azure.healthinsights.clinicalmatching.models package

class azure.healthinsights.clinicalmatching.models.AcceptedAge(*args: Any, **kwargs: Any)[source]

A person’s age, given as a number (value) and a unit (e.g. years, months).

All required parameters must be populated in order to send to Azure.

Variables

  • unit (str or AgeUnit) – Possible units for a person’s age. Required. Known values are: “years”, “months”, and “days”.

  • value (float) – The number of years/months/days that represents the person’s age. Required.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
unit: Union[str, _models.AgeUnit]

“years”, “months”, and “days”.

Type

Possible units for a person’s age. Required. Known values are

value: float

The number of years/months/days that represents the person’s age. Required.

class azure.healthinsights.clinicalmatching.models.AcceptedAgeRange(*args: Any, **kwargs: Any)[source]

A definition of the range of ages accepted by a clinical trial. Contains a minimum age and/or a maximum age.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
maximum_age: Optional[_models.AcceptedAge]

A person’s age, given as a number (value) and a unit (e.g. years, months).

minimum_age: Optional[_models.AcceptedAge]

A person’s age, given as a number (value) and a unit (e.g. years, months).

class azure.healthinsights.clinicalmatching.models.AgeUnit(value)[source]

Possible units for a person’s age.

DAYS = 'days'
MONTHS = 'months'
YEARS = 'years'
class azure.healthinsights.clinicalmatching.models.AreaGeometry(*args: Any, **kwargs: Any)[source]

GeoJSON geometry, representing the area circle’s center.

All required parameters must be populated in order to send to Azure.

Variables

  • type (str or GeoJsonGeometryType) – GeoJSON geometry type. Required. “Point”

  • coordinates (list[float]) – Coordinates of the area circle’s center, represented according to the GeoJSON standard. This is an array of 2 decimal numbers, longitude and latitude (precisely in this order). Required.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
coordinates: List[float]

Coordinates of the area circle’s center, represented according to the GeoJSON standard. This is an array of 2 decimal numbers, longitude and latitude (precisely in this order). Required.

type: Union[str, _models.GeoJsonGeometryType]

GeoJSON geometry type. Required. “Point”

class azure.healthinsights.clinicalmatching.models.AreaProperties(*args: Any, **kwargs: Any)[source]

GeoJSON object properties.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
radius: float

The radius of the area’s circle, in meters. Required.

sub_type: Union[str, _models.GeoJsonPropertiesSubType]

GeoJSON object sub-type. Required. “Circle”

class azure.healthinsights.clinicalmatching.models.ClinicalCodedElement(*args: Any, **kwargs: Any)[source]

A piece of clinical information, expressed as a code in a clinical coding system.

All required parameters must be populated in order to send to Azure.

Variables

  • system (str) – The clinical coding system, e.g. ICD-10, SNOMED-CT, UMLS. Required.

  • code (str) – The code within the given clinical coding system. Required.

  • name (str) – The name of this coded concept in the coding system.

  • value (str) – A value associated with the code within the given clinical coding system.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
code: str

The code within the given clinical coding system. Required.

name: Optional[str]

The name of this coded concept in the coding system.

system: str

The clinical coding system, e.g. ICD-10, SNOMED-CT, UMLS. Required.

value: Optional[str]

A value associated with the code within the given clinical coding system.

class azure.healthinsights.clinicalmatching.models.ClinicalDocumentType(value)[source]

The type of the clinical document.

CONSULTATION = 'consultation'
DISCHARGE_SUMMARY = 'dischargeSummary'
HISTORY_AND_PHYSICAL = 'historyAndPhysical'
IMAGING = 'imaging'
LABORATORY = 'laboratory'
PATHOLOGY = 'pathology'
PROCEDURE = 'procedure'
PROGRESS = 'progress'
class azure.healthinsights.clinicalmatching.models.ClinicalNoteEvidence(*args: Any, **kwargs: Any)[source]

A piece of evidence from a clinical note (text document).

All required parameters must be populated in order to send to Azure.

Variables

  • id (str) – The identifier of the document containing the evidence. Required.

  • text (str) – The actual text span which is evidence for the inference.

  • offset (int) – The start index of the evidence text span in the document (0 based). Required.

  • length (int) – The length of the evidence text span. Required.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
id: str

The identifier of the document containing the evidence. Required.

length: int

The length of the evidence text span. Required.

offset: int

The start index of the evidence text span in the document (0 based). Required.

text: Optional[str]

The actual text span which is evidence for the inference.

class azure.healthinsights.clinicalmatching.models.ClinicalTrialAcceptedSex(value)[source]

Possible values for the Sex eligibility criterion as accepted by clinical trials, which indicates the sex of people who may participate in a clinical study.

ALL = 'all'
FEMALE = 'female'
MALE = 'male'
class azure.healthinsights.clinicalmatching.models.ClinicalTrialDemographics(*args: Any, **kwargs: Any)[source]

Demographic criteria for a clinical trial.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
accepted_age_range: Optional[_models.AcceptedAgeRange]

A definition of the range of ages accepted by a clinical trial. Contains a minimum age and/or a maximum age.

accepted_sex: Optional[Union[str, _models.ClinicalTrialAcceptedSex]]

“all”, “female”, and “male”.

Type

Indication of the sex of people who may participate in the clinical trial. Known values are

class azure.healthinsights.clinicalmatching.models.ClinicalTrialDetails(*args: Any, **kwargs: Any)[source]

A description of a clinical trial.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
demographics: Optional[_models.ClinicalTrialDemographics]

Demographic criteria for a clinical trial.

eligibility_criteria_text: Optional[str]

The eligibility criteria of the clinical trial (inclusion and exclusion), given as text.

id: str

A given identifier for the clinical trial. Has to be unique within a list of clinical trials. Required.

metadata: _models.ClinicalTrialMetadata

Trial data which is of interest to the potential participant. Required.

class azure.healthinsights.clinicalmatching.models.ClinicalTrialMetadata(*args: Any, **kwargs: Any)[source]

Trial data which is of interest to the potential participant.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
conditions: List[str]

Medical conditions and their synonyms which are relevant for the clinical trial, given as strings. Required.

contacts: Optional[List[_models.ContactDetails]]

Contact details of the trial administrators, for patients that want to participate in the trial.

facilities: Optional[List[_models.ClinicalTrialResearchFacility]]

Research facilities where the clinical trial is conducted.

phases: Optional[List[Union[str, _models.ClinicalTrialPhase]]]

Phases which are relevant for the clinical trial. Each clinical trial can be in a certain phase or in multiple phases.

recruitment_status: Optional[Union[str, _models.ClinicalTrialRecruitmentStatus]]

“unknownStatus”, “notYetRecruiting”, “recruiting”, and “enrollingByInvitation”.

Type

Possible recruitment status of a clinical trial. Known values are

sponsors: Optional[List[str]]

Sponsors/collaborators involved with the trial.

study_type: Optional[Union[str, _models.ClinicalTrialStudyType]]

“interventional”, “observational”, “expandedAccess”, and “patientRegistries”.

Type

Possible study types of a clinical trial. Known values are

class azure.healthinsights.clinicalmatching.models.ClinicalTrialPhase(value)[source]

Possible phases of a clinical trial.

EARLY_PHASE1 = 'earlyPhase1'
NOT_APPLICABLE = 'notApplicable'
PHASE1 = 'phase1'
PHASE2 = 'phase2'
PHASE3 = 'phase3'
PHASE4 = 'phase4'
class azure.healthinsights.clinicalmatching.models.ClinicalTrialPurpose(value)[source]

Possible purposes of a clinical trial.

BASIC_SCIENCE = 'basicScience'
DEVICE_FEASIBILITY = 'deviceFeasibility'
DIAGNOSTIC = 'diagnostic'
HEALTH_SERVICES_RESEARCH = 'healthServicesResearch'
NOT_APPLICABLE = 'notApplicable'
OTHER = 'other'
PREVENTION = 'prevention'
SCREENING = 'screening'
SUPPORTIVE_CARE = 'supportiveCare'
TREATMENT = 'treatment'
class azure.healthinsights.clinicalmatching.models.ClinicalTrialRecruitmentStatus(value)[source]

Possible recruitment status of a clinical trial.

ENROLLING_BY_INVITATION = 'enrollingByInvitation'
NOT_YET_RECRUITING = 'notYetRecruiting'
RECRUITING = 'recruiting'
UNKNOWN_STATUS = 'unknownStatus'
class azure.healthinsights.clinicalmatching.models.ClinicalTrialRegistryFilter(*args: Any, **kwargs: Any)[source]

A filter defining a subset of clinical trials from a given clinical trial registry (e.g. clinicaltrials.gov).

Variables

  • conditions (list[str]) – Trials with any of the given medical conditions will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the medical conditions.

  • study_types (list[str or ClinicalTrialStudyType]) – Trials with any of the given study types will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the study types.

  • recruitment_statuses (list[str or ClinicalTrialRecruitmentStatus]) – Trials with any of the given recruitment statuses will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the recruitment statuses.

  • sponsors (list[str]) – Trials with any of the given sponsors will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the sponsors.

  • phases (list[str or ClinicalTrialPhase]) – Trials with any of the given phases will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the phases.

  • purposes (list[str or ClinicalTrialPurpose]) – Trials with any of the given purposes will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the purposes.

  • ids (list[str]) – Trials with any of the given identifiers will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial identifiers.

  • sources (list[str or ClinicalTrialSource]) – Trials with any of the given sources will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the sources.

  • facility_names (list[str]) – Trials with any of the given facility names will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial facility names.

  • facility_locations (list[GeographicLocation]) – Trials with any of the given facility locations will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial facility locations.

  • facility_areas (list[GeographicArea]) – Trials with any of the given facility area boundaries will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial facility area boundaries.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
conditions: Optional[List[str]]

Trials with any of the given medical conditions will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the medical conditions.

facility_areas: Optional[List[_models.GeographicArea]]

Trials with any of the given facility area boundaries will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial facility area boundaries.

facility_locations: Optional[List[_models.GeographicLocation]]

Trials with any of the given facility locations will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial facility locations.

facility_names: Optional[List[str]]

Trials with any of the given facility names will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial facility names.

ids: Optional[List[str]]

Trials with any of the given identifiers will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the trial identifiers.

phases: Optional[List[Union[str, _models.ClinicalTrialPhase]]]

Trials with any of the given phases will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the phases.

purposes: Optional[List[Union[str, _models.ClinicalTrialPurpose]]]

Trials with any of the given purposes will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the purposes.

recruitment_statuses: Optional[List[Union[str, _models.ClinicalTrialRecruitmentStatus]]]

Trials with any of the given recruitment statuses will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the recruitment statuses.

sources: Optional[List[Union[str, _models.ClinicalTrialSource]]]

Trials with any of the given sources will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the sources.

sponsors: Optional[List[str]]

Trials with any of the given sponsors will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the sponsors.

study_types: Optional[List[Union[str, _models.ClinicalTrialStudyType]]]

Trials with any of the given study types will be included in the selection (provided that other limitations are satisfied). Leaving this list empty will not limit the study types.

class azure.healthinsights.clinicalmatching.models.ClinicalTrialResearchFacility(*args: Any, **kwargs: Any)[source]

Details of a research facility where a clinical trial is conducted.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
city: Optional[str]

City name.

country_or_region: str

Country/region name. Required.

name: str

The facility’s name. Required.

state: Optional[str]

State name.

class azure.healthinsights.clinicalmatching.models.ClinicalTrialSource(value)[source]

Possible sources of a clinical trial.

CLINICALTRIALS_GOV = 'clinicaltrials.gov'
CUSTOM = 'custom'
class azure.healthinsights.clinicalmatching.models.ClinicalTrialStudyType(value)[source]

Possible study types of a clinical trial.

EXPANDED_ACCESS = 'expandedAccess'
INTERVENTIONAL = 'interventional'
OBSERVATIONAL = 'observational'
PATIENT_REGISTRIES = 'patientRegistries'
class azure.healthinsights.clinicalmatching.models.ClinicalTrials(*args: Any, **kwargs: Any)[source]

The clinical trials that the patient(s) should be matched to. The trial selection can be given as a list of custom clinical trials and/or a list of filters to known clinical trial registries. In case both are given, the resulting trial set is a union of the two sets.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
custom_trials: Optional[List[_models.ClinicalTrialDetails]]

A list of clinical trials.

registry_filters: Optional[List[_models.ClinicalTrialRegistryFilter]]

A list of filters, each one creating a selection of trials from a given clinical trial registry.

class azure.healthinsights.clinicalmatching.models.ContactDetails(*args: Any, **kwargs: Any)[source]

A person’s contact details.

Variables

  • name (str) – The person’s name.

  • email (str) – The person’s email.

  • phone (str) – A person’s phone number.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
email: Optional[str]

The person’s email.

name: Optional[str]

The person’s name.

phone: Optional[str]

A person’s phone number.

class azure.healthinsights.clinicalmatching.models.DocumentContent(*args: Any, **kwargs: Any)[source]

The content of the patient document.

All required parameters must be populated in order to send to Azure.

Variables

  • source_type (str or DocumentContentSourceType) – The type of the content’s source. In case the source type is ‘inline’, the content is given as a string (for instance, text). In case the source type is ‘reference’, the content is given as a URI. Required. Known values are: “inline” and “reference”.

  • value (str) – The content of the document, given either inline (as a string) or as a reference (URI). Required.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
source_type: Union[str, _models.DocumentContentSourceType]

The type of the content’s source. In case the source type is ‘inline’, the content is given as a string (for instance, text). In case the source type is ‘reference’, the content is given as a URI. Required. Known values are: “inline” and “reference”.

value: str

The content of the document, given either inline (as a string) or as a reference (URI). Required.

class azure.healthinsights.clinicalmatching.models.DocumentContentSourceType(value)[source]

The type of the content’s source. In case the source type is ‘inline’, the content is given as a string (for instance, text). In case the source type is ‘reference’, the content is given as a URI.

INLINE = 'inline'
REFERENCE = 'reference'
class azure.healthinsights.clinicalmatching.models.DocumentType(value)[source]

The type of the patient document, such as ‘note’ (text document) or ‘fhirBundle’ (FHIR JSON document).

DICOM = 'dicom'
FHIR_BUNDLE = 'fhirBundle'
GENOMIC_SEQUENCING = 'genomicSequencing'
NOTE = 'note'
class azure.healthinsights.clinicalmatching.models.Error(*args: Any, **kwargs: Any)[source]

The error object.

All required parameters must be populated in order to send to Azure.

Variables

  • code (str) – One of a server-defined set of error codes. Required.

  • message (str) – A human-readable representation of the error. Required.

  • target (str) – The target of the error.

  • details (list[Error]) – An array of details about specific errors that led to this reported error. Required.

  • innererror (InnerError) – An object containing more specific information than the current object about the error.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
code: str

One of a server-defined set of error codes. Required.

details: List[_models.Error]

An array of details about specific errors that led to this reported error. Required.

innererror: Optional[_models.InnerError]

An object containing more specific information than the current object about the error.

message: str

A human-readable representation of the error. Required.

target: Optional[str]

The target of the error.

class azure.healthinsights.clinicalmatching.models.ExtendedClinicalCodedElement(*args: Any, **kwargs: Any)[source]

A piece of clinical information, expressed as a code in a clinical coding system, extended by semantic information.

All required parameters must be populated in order to send to Azure.

Variables

  • system (str) – The clinical coding system, e.g. ICD-10, SNOMED-CT, UMLS. Required.

  • code (str) – The code within the given clinical coding system. Required.

  • name (str) – The name of this coded concept in the coding system.

  • value (str) – A value associated with the code within the given clinical coding system.

  • semantic_type (str) – The UMLS semantic type associated with the coded concept.

  • category (str) – The bio-medical category related to the coded concept, e.g. Diagnosis, Symptom, Medication, Examination.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
category: Optional[str]

The bio-medical category related to the coded concept, e.g. Diagnosis, Symptom, Medication, Examination.

code: str

The code within the given clinical coding system. Required.

name: Optional[str]

The name of this coded concept in the coding system.

semantic_type: Optional[str]

//www.nlm.nih.gov/research/umls/META3_current_semantic_types.html>`_ associated with the coded concept.

Type

The `UMLS semantic type <https

system: str

The clinical coding system, e.g. ICD-10, SNOMED-CT, UMLS. Required.

value: Optional[str]

A value associated with the code within the given clinical coding system.

class azure.healthinsights.clinicalmatching.models.GeoJsonGeometryType(value)[source]

GeoJSON geometry type.

POINT = 'Point'
class azure.healthinsights.clinicalmatching.models.GeoJsonPropertiesSubType(value)[source]

GeoJSON object sub-type.

CIRCLE = 'Circle'
class azure.healthinsights.clinicalmatching.models.GeoJsonType(value)[source]

GeoJSON type.

FEATURE = 'Feature'
class azure.healthinsights.clinicalmatching.models.GeographicArea(*args: Any, **kwargs: Any)[source]

A geographic area, expressed as a Circle geometry represented using a GeoJSON Feature (see GeoJSON spec ).

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
geometry: _models.AreaGeometry

GeoJSON geometry, representing the area circle’s center. Required.

properties: _models.AreaProperties

GeoJSON object properties. Required.

type: Union[str, _models.GeoJsonType]

GeoJSON type. Required. “Feature”

class azure.healthinsights.clinicalmatching.models.GeographicLocation(*args: Any, **kwargs: Any)[source]

A location given as a combination of city, state and country/region. It could specify a city, a state or a country/region. In case a city is specified, either state +country/region or country/region (for countries/regions where there are no states) should be added. In case a state is specified (without a city), country/region should be added.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
city: Optional[str]

City name.

country_or_region: str

Country/region name. Required.

state: Optional[str]

State name.

class azure.healthinsights.clinicalmatching.models.InnerError(*args: Any, **kwargs: Any)[source]

An object containing more specific information about the error. As per Microsoft One API guidelines - https://github.com/Microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
code: str

One of a server-defined set of error codes. Required.

innererror: Optional[_models.InnerError]

Inner error.

class azure.healthinsights.clinicalmatching.models.JobStatus(value)[source]

The status of the processing job.

FAILED = 'failed'
NOT_STARTED = 'notStarted'
PARTIALLY_COMPLETED = 'partiallyCompleted'
RUNNING = 'running'
SUCCEEDED = 'succeeded'
class azure.healthinsights.clinicalmatching.models.PatientDocument(*args: Any, **kwargs: Any)[source]

A clinical document related to a patient. Document here is in the wide sense - not just a text document (note).

All required parameters must be populated in order to send to Azure.

Variables

  • type (str or DocumentType) – The type of the patient document, such as ‘note’ (text document) or ‘fhirBundle’ (FHIR JSON document). Required. Known values are: “note”, “fhirBundle”, “dicom”, and “genomicSequencing”.

  • clinical_type (str or ClinicalDocumentType) – The type of the clinical document. Known values are: “consultation”, “dischargeSummary”, “historyAndPhysical”, “procedure”, “progress”, “imaging”, “laboratory”, and “pathology”.

  • id (str) – A given identifier for the document. Has to be unique across all documents for a single patient. Required.

  • language (str) – A 2 letter ISO 639-1 representation of the language of the document.

  • created_date_time (datetime) – The date and time when the document was created.

  • content (DocumentContent) – The content of the patient document. Required.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
clinical_type: Optional[Union[str, _models.ClinicalDocumentType]]

“consultation”, “dischargeSummary”, “historyAndPhysical”, “procedure”, “progress”, “imaging”, “laboratory”, and “pathology”.

Type

The type of the clinical document. Known values are

content: _models.DocumentContent

The content of the patient document. Required.

created_date_time: Optional[datetime.datetime]

The date and time when the document was created.

id: str

A given identifier for the document. Has to be unique across all documents for a single patient. Required.

language: Optional[str]

A 2 letter ISO 639-1 representation of the language of the document.

type: Union[str, _models.DocumentType]

The type of the patient document, such as ‘note’ (text document) or ‘fhirBundle’ (FHIR JSON document). Required. Known values are: “note”, “fhirBundle”, “dicom”, and “genomicSequencing”.

class azure.healthinsights.clinicalmatching.models.PatientInfo(*args: Any, **kwargs: Any)[source]

Patient structured information, including demographics and known structured clinical information.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
birth_date: Optional[datetime.date]

The patient’s date of birth.

clinical_info: Optional[List[_models.ClinicalCodedElement]]

Known clinical information for the patient, structured.

sex: Optional[Union[str, _models.PatientInfoSex]]

“female”, “male”, and “unspecified”.

Type

The patient’s sex. Known values are

class azure.healthinsights.clinicalmatching.models.PatientInfoSex(value)[source]

The patient’s sex.

FEMALE = 'female'
MALE = 'male'
UNSPECIFIED = 'unspecified'
class azure.healthinsights.clinicalmatching.models.PatientRecord(*args: Any, **kwargs: Any)[source]

A patient record, including their clinical information and data.

All required parameters must be populated in order to send to Azure.

Variables

  • id (str) – A given identifier for the patient. Has to be unique across all patients in a single request. Required.

  • info (PatientInfo) – Patient structured information, including demographics and known structured clinical information.

  • data (list[PatientDocument]) – Patient unstructured clinical data, given as documents.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
data: Optional[List[_models.PatientDocument]]

Patient unstructured clinical data, given as documents.

id: str

A given identifier for the patient. Has to be unique across all patients in a single request. Required.

info: Optional[_models.PatientInfo]

Patient structured information, including demographics and known structured clinical information.

class azure.healthinsights.clinicalmatching.models.RepeatabilityResultType(value)[source]

Type of RepeatabilityResultType.

ACCEPTED = 'accepted'
REJECTED = 'rejected'
class azure.healthinsights.clinicalmatching.models.TrialMatcherData(*args: Any, **kwargs: Any)[source]

TrialMatcherData.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
configuration: Optional[_models.TrialMatcherModelConfiguration]

Configuration affecting the Trial Matcher model’s inference.

patients: List[_models.PatientRecord]

The list of patients, including their clinical information and data. Required.

class azure.healthinsights.clinicalmatching.models.TrialMatcherInference(*args: Any, **kwargs: Any)[source]

An inference made by the Trial Matcher model regarding a patient.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
confidence_score: Optional[float]

Confidence score for this inference.

description: Optional[str]

The description corresponding to the inference value.

evidence: Optional[List[_models.TrialMatcherInferenceEvidence]]

The evidence corresponding to the inference value.

id: Optional[str]

The identifier of the clinical trial.

metadata: Optional[_models.ClinicalTrialMetadata]

Trial data which is of interest to the potential participant.

source: Optional[Union[str, _models.ClinicalTrialSource]]

“custom” and “clinicaltrials.gov”.

Type

Possible sources of a clinical trial. Known values are

type: Union[str, _models.TrialMatcherInferenceType]

The type of the Trial Matcher inference. Required. “trialEligibility”

value: str

The value of the inference, as relevant for the given inference type. Required.

class azure.healthinsights.clinicalmatching.models.TrialMatcherInferenceEvidence(*args: Any, **kwargs: Any)[source]

A piece of evidence corresponding to a Trial Matcher inference.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
eligibility_criteria_evidence: Optional[str]

A piece of evidence from the eligibility criteria text of a clinical trial.

importance: Optional[float]

A value indicating how important this piece of evidence is for the inference.

patient_data_evidence: Optional[_models.ClinicalNoteEvidence]

A piece of evidence from a clinical note (text document).

patient_info_evidence: Optional[_models.ClinicalCodedElement]

A piece of clinical information, expressed as a code in a clinical coding system.

class azure.healthinsights.clinicalmatching.models.TrialMatcherInferenceType(value)[source]

The type of the Trial Matcher inference.

TRIAL_ELIGIBILITY = 'trialEligibility'
class azure.healthinsights.clinicalmatching.models.TrialMatcherModelConfiguration(*args: Any, **kwargs: Any)[source]

Configuration affecting the Trial Matcher model’s inference.

All required parameters must be populated in order to send to Azure.

Variables

  • verbose (bool) – An indication whether the model should produce verbose output.

  • include_evidence (bool) – An indication whether the model’s output should include evidence for the inferences.

  • clinical_trials (ClinicalTrials) – The clinical trials that the patient(s) should be matched to. :code:`<br />`The trial selection can be given as a list of custom clinical trials and/or a list of filters to known clinical trial registries. In case both are given, the resulting trial set is a union of the two sets. Required.

clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
clinical_trials: _models.ClinicalTrials

The clinical trials that the patient(s) should be matched to. :code:`<br />`The trial selection can be given as a list of custom clinical trials and/or a list of filters to known clinical trial registries. In case both are given, the resulting trial set is a union of the two sets. Required.

include_evidence: bool

An indication whether the model’s output should include evidence for the inferences.

verbose: bool

An indication whether the model should produce verbose output.

class azure.healthinsights.clinicalmatching.models.TrialMatcherPatientResult(*args: Any, **kwargs: Any)[source]

The results of the model’s work for a single patient.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
id: str

The identifier given for the patient in the request. Required.

inferences: List[_models.TrialMatcherInference]

The model’s inferences for the given patient. Required.

needed_clinical_info: Optional[List[_models.ExtendedClinicalCodedElement]]

Clinical information which is needed to provide better trial matching results for the patient. Clinical information which is needed to provide better trial matching results for the patient.

class azure.healthinsights.clinicalmatching.models.TrialMatcherResult(*args: Any, **kwargs: Any)[source]

The response for the Trial Matcher request.

Readonly variables are only populated by the server, and will be ignored when sending a request.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
created_date_time: datetime.datetime

The date and time when the processing job was created. Required.

errors: Optional[List[_models.Error]]

An array of errors, if any errors occurred during the processing job.

expiration_date_time: datetime.datetime

The date and time when the processing job is set to expire. Required.

job_id: str

A processing job identifier. Required.

last_update_date_time: datetime.datetime

The date and time when the processing job was last updated. Required.

results: Optional[_models.TrialMatcherResults]

The inference results for the Trial Matcher request.

status: Union[str, _models.JobStatus]

“notStarted”, “running”, “succeeded”, “failed”, and “partiallyCompleted”.

Type

The status of the processing job. Required. Known values are

class azure.healthinsights.clinicalmatching.models.TrialMatcherResults(*args: Any, **kwargs: Any)[source]

The inference results for the Trial Matcher request.

All required parameters must be populated in order to send to Azure.

Variables
clear() → None.  Remove all items from D.
copy() → azure.healthinsights.clinicalmatching._model_base.Model
get(k[, d]) → D[k] if k in D, else d.  d defaults to None.
items() → a set-like object providing a view on D’s items
keys() → a set-like object providing a view on D’s keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair

as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D
update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

values() → an object providing a view on D’s values
knowledge_graph_last_update_date: Optional[datetime.date]

The date when the clinical trials knowledge graph was last updated.

model_version: str

The version of the model used for inference, expressed as the model date. Required.

patients: List[_models.TrialMatcherPatientResult]

Results for the patients given in the request. Required.