Index
-
NlpService(interface) -
AnalyzeEntitiesRequest(message) -
AnalyzeEntitiesRequest.AlternativeOutputFormat(enum) -
AnalyzeEntitiesRequest.LicensedVocabulary(enum) -
AnalyzeEntitiesResponse(message) -
Entity(message) -
EntityMention(message) -
EntityMention.Feature(message) -
EntityMention.LinkedEntity(message) -
EntityMentionRelationship(message) -
TextSpan(message)
NlpService
A service to analyzing healthcare documents.
rpc AnalyzeEntities(
AnalyzeEntitiesRequest
) returns ( AnalyzeEntitiesResponse
)
Analyze heathcare entity in a document. Its response includes the recognized entity mentions and the relationships between them. AnalyzeEntities uses context aware models to detect entities. This method can only analyze documents written in English.
- Authorization scopes
-
Requires one of the following OAuth scopes:
-
https://www.googleapis.com/auth/cloud-healthcare -
https://www.googleapis.com/auth/cloud-platform
For more information, see the Authentication Overview .
-
AnalyzeEntitiesRequest
The request to analyze healthcare entities in a document.
| Fields | |
|---|---|
nlp_service
|
The resource name of the service of the form: "projects/{project_id}/locations/{location_id}/services/nlp". |
document_content
|
document_content is a document to be annotated. |
licensed_vocabularies[]
|
A list of licensed vocabularies to use in the request, in addition to the default unlicensed vocabularies. |
alternative_output_format
|
Optional. Alternative output format to be generated based on the results of analysis. |
AlternativeOutputFormat
Predefined list of available alternative output formats
| Enums | |
|---|---|
ALTERNATIVE_OUTPUT_FORMAT_UNSPECIFIED
|
No alternative output format is specified. |
FHIR_BUNDLE
|
FHIR bundle output. |
LicensedVocabulary
Predefined list of available licensed vocabularies
| Enums | |
|---|---|
LICENSED_VOCABULARY_UNSPECIFIED
|
No licensed vocabulary specified. |
ICD10CM
|
ICD-10-CM vocabulary |
SNOMEDCT_US
|
SNOMED CT (US version) vocabulary |
AnalyzeEntitiesResponse
Includes recognized entity mentions and relationships between them.
entity_mentions[]
The entity_mentions
field contains all the annotated medical entities that were mentioned in the provided document.
entities[]
The union of all the candidate entities that the entity_mentions in this response could link to. These are UMLS concepts or normalized mention content.
relationships[]
relationships contains all the binary relationships that were identified between entity mentions within the provided document.
alternative_output_format
. The alternative supported format if the config was included in the request. alternative_output_format
can be only one of the following:fhir_bundle
string
The FHIR bundle ( R4
) that includes all the entities, the entity mentions, and the relationships in JSON format.
Entity
The candidate entities that an entity mention could link to.
| Fields | |
|---|---|
entity_id
|
entity_id is a first class field entity_id uniquely identifies this concept and its meta-vocabulary. For example, "UMLS/C0000970". |
preferred_term
|
preferred_term is the preferred term for this concept. For example, "Acetaminophen". For ad hoc entities formed by normalization, this is the most popular unnormalized string. |
vocabulary_codes[]
|
Vocabulary codes are first-class fields and differentiated from the concept unique identifier (entity_id). vocabulary_codes contains the representation of this concept in particular vocabularies, such as ICD-10, SNOMED-CT and RxNORM. These are prefixed by the name of the vocabulary, followed by the unique code within that vocabulary. For example, "RXNORM/A10334543". |
EntityMention
An entity mention in the document.
| Fields | |
|---|---|
mention_id
|
mention_id uniquely identifies each entity mention in a single response. |
type
|
The semantic type of the entity: UNKNOWN_ENTITY_TYPE, ALONE, ANATOMICAL_STRUCTURE, ASSISTED_LIVING, BF_RESULT, BM_RESULT, BM_UNIT, BM_VALUE, BODY_FUNCTION, BODY_MEASUREMENT, COMPLIANT, DOESNOT_FOLLOWUP, FAMILY, FOLLOWSUP, LABORATORY_DATA, LAB_RESULT, LAB_UNIT, LAB_VALUE, MEDICAL_DEVICE, MEDICINE, MED_DOSE, MED_DURATION, MED_FORM, MED_FREQUENCY, MED_ROUTE, MED_STATUS, MED_STRENGTH, MED_TOTALDOSE, MED_UNIT, NON_COMPLIANT, OTHER_LIVINGSTATUS, PROBLEM, PROCEDURE, PROCEDURE_RESULT, PROC_METHOD, REASON_FOR_NONCOMPLIANCE, SEVERITY, SUBSTANCE_ABUSE, UNCLEAR_FOLLOWUP. |
text
|
text is the location of the entity mention in the document. |
linked_entities[]
|
linked_entities are candidate ontological concepts that this entity mention may refer to. They are sorted by decreasing confidence. |
temporal_assessment
|
How this entity mention relates to the subject temporally. Its value is one of: CURRENT, CLINICAL_HISTORY, FAMILY_HISTORY, UPCOMING, ALLERGY |
certainty_assessment
|
The certainty assessment of the entity mention. Its value is one of: LIKELY, SOMEWHAT_LIKELY, UNCERTAIN, SOMEWHAT_UNLIKELY, UNLIKELY, CONDITIONAL |
subject
|
The subject this entity mention relates to. Its value is one of: PATIENT, FAMILY_MEMBER, OTHER |
confidence
|
The model's confidence in this entity mention annotation. A number between 0 and 1. |
additional_info[]
|
Additional information about the entity mention. For example, for an entity mention of type |
Feature
A feature of an entity mention.
| Fields | |
|---|---|
value
|
The value of this feature annotation. Its range depends on the type of the feature. |
confidence
|
The model's confidence in this feature annotation. A number between 0 and 1. |
LinkedEntity
EntityMentions can be linked to multiple entities using a LinkedEntity message lets us add other fields, e.g. confidence.
| Fields | |
|---|---|
entity_id
|
entity_id is a concept unique identifier. These are prefixed by a string that identifies the entity coding system, followed by the unique identifier within that system. For example, "UMLS/C0000970". This also supports ad hoc entities, which are formed by normalizing entity mention content. |
EntityMentionRelationship
Defines directed relationship from one entity mention to another.
| Fields | |
|---|---|
subject_id
|
subject_id is the id of the subject entity mention. |
object_id
|
object_id is the id of the object entity mention. |
confidence
|
The model's confidence in this annotation. A number between 0 and 1. |
TextSpan
A span of text in the provided document.
| Fields | |
|---|---|
content
|
The original text contained in this span. |
begin_offset
|
The unicode codepoint index of the beginning of this span. |
