chore: Update discovery artifacts (#1523)
## Deleted keys were detected in the following stable discovery artifacts:
displayvideo v1 https://github.com/googleapis/google-api-python-client/commit/22caa4f2f8ecb0f0ad6cfac547f9deb76fdcbebb
memcache v1 https://github.com/googleapis/google-api-python-client/commit/393dce7a3e584ad6be58c832ec826fe3b44e353b
## Deleted keys were detected in the following pre-stable discovery artifacts:
memcache v1beta2 https://github.com/googleapis/google-api-python-client/commit/393dce7a3e584ad6be58c832ec826fe3b44e353b
## Discovery Artifact Change Summary:
feat(apigee): update the api https://github.com/googleapis/google-api-python-client/commit/0e4fed7f1e08a616cbc81243c24391bc20ce5edb
feat(bigquery): update the api https://github.com/googleapis/google-api-python-client/commit/04e112ce89d6ddb3aeaae889c2de36070d6c2814
feat(bigtableadmin): update the api https://github.com/googleapis/google-api-python-client/commit/6b77931c3c9aba59d5b326c570a2080252c8beb1
feat(cloudprofiler): update the api https://github.com/googleapis/google-api-python-client/commit/3009ee3c238ae1fa51c529e9f187ec26693138a4
feat(container): update the api https://github.com/googleapis/google-api-python-client/commit/e5d01ecee51da0c7a2543b833a1395a94c27bef6
feat(dataproc): update the api https://github.com/googleapis/google-api-python-client/commit/fec73562a93b5a532bce6c91f0d30ec4fbd54ddb
feat(displayvideo): update the api https://github.com/googleapis/google-api-python-client/commit/22caa4f2f8ecb0f0ad6cfac547f9deb76fdcbebb
feat(documentai): update the api https://github.com/googleapis/google-api-python-client/commit/444836b9afe8d3eb8d52a1431652bfda1ad3288b
feat(healthcare): update the api https://github.com/googleapis/google-api-python-client/commit/2f3173aa4b4d154c909eea853a0c4c306834e0ab
feat(ideahub): update the api https://github.com/googleapis/google-api-python-client/commit/8ebf9d2bd419561d5eacb78823aa1fc519fe2710
feat(memcache): update the api https://github.com/googleapis/google-api-python-client/commit/393dce7a3e584ad6be58c832ec826fe3b44e353b
feat(mybusinesslodging): update the api https://github.com/googleapis/google-api-python-client/commit/c51a0d15e634c2ab1c7762533f33d59f10b01875
feat(speech): update the api https://github.com/googleapis/google-api-python-client/commit/bf6e86f6ee8c3985e1ce6f0475ef4f8685b52060
feat(streetviewpublish): update the api https://github.com/googleapis/google-api-python-client/commit/c8cf30cd67f5588d7cbe60631e42f0a49ea6c307
feat(youtube): update the api https://github.com/googleapis/google-api-python-client/commit/855cbfea1f6d46af07c4b80ab26fc30ca46370b7
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+<html><body>
+<style>
+
+body, h1, h2, h3, div, span, p, pre, a {
+ margin: 0;
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+ font-weight: inherit;
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+ font-size: 100%;
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+ border-bottom: solid #CCC 1px;
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+ margin-top: 0.5em;
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+
+.firstline {
+ margin-left: 2 em;
+}
+
+.method {
+ margin-top: 1em;
+ border: solid 1px #CCC;
+ padding: 1em;
+ background: #EEE;
+}
+
+.details {
+ font-weight: bold;
+ font-size: 14px;
+}
+
+</style>
+
+<h1><a href="healthcare_v1.html">Cloud Healthcare API</a> . <a href="healthcare_v1.projects.html">projects</a> . <a href="healthcare_v1.projects.locations.html">locations</a> . <a href="healthcare_v1.projects.locations.services.html">services</a> . <a href="healthcare_v1.projects.locations.services.nlp.html">nlp</a></h1>
+<h2>Instance Methods</h2>
+<p class="toc_element">
+ <code><a href="#analyzeEntities">analyzeEntities(nlpService, body=None, x__xgafv=None)</a></code></p>
+<p class="firstline">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.</p>
+<p class="toc_element">
+ <code><a href="#close">close()</a></code></p>
+<p class="firstline">Close httplib2 connections.</p>
+<h3>Method Details</h3>
+<div class="method">
+ <code class="details" id="analyzeEntities">analyzeEntities(nlpService, body=None, x__xgafv=None)</code>
+ <pre>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.
+
+Args:
+ nlpService: string, The resource name of the service of the form: "projects/{project_id}/locations/{location_id}/services/nlp". (required)
+ body: object, The request body.
+ The object takes the form of:
+
+{ # The request to analyze healthcare entities in a document.
+ "documentContent": "A String", # document_content is a document to be annotated.
+ "licensedVocabularies": [ # A list of licensed vocabularies to use in the request, in addition to the default unlicensed vocabularies.
+ "A String",
+ ],
+}
+
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # Includes recognized entity mentions and relationships between them.
+ "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.
+ { # The candidate entities that an entity mention could link to.
+ "entityId": "A String", # entity_id is a first class field entity_id uniquely identifies this concept and its meta-vocabulary. For example, "UMLS/C0000970".
+ "preferredTerm": "A String", # 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.
+ "vocabularyCodes": [ # 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".
+ "A String",
+ ],
+ },
+ ],
+ "entityMentions": [ # entity_mentions contains all the annotated medical entities that were mentioned in the provided document.
+ { # An entity mention in the document.
+ "certaintyAssessment": { # A feature of an entity mention. # The certainty assessment of the entity mention. Its value is one of: LIKELY, SOMEWHAT_LIKELY, UNCERTAIN, SOMEWHAT_UNLIKELY, UNLIKELY, CONDITIONAL
+ "confidence": 3.14, # The model's confidence in this feature annotation. A number between 0 and 1.
+ "value": "A String", # The value of this feature annotation. Its range depends on the type of the feature.
+ },
+ "confidence": 3.14, # The model's confidence in this entity mention annotation. A number between 0 and 1.
+ "linkedEntities": [ # linked_entities are candidate ontological concepts that this entity mention may refer to. They are sorted by decreasing confidence.it
+ { # EntityMentions can be linked to multiple entities using a LinkedEntity message lets us add other fields, e.g. confidence.
+ "entityId": "A String", # 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.
+ },
+ ],
+ "mentionId": "A String", # mention_id uniquely identifies each entity mention in a single response.
+ "subject": { # A feature of an entity mention. # The subject this entity mention relates to. Its value is one of: PATIENT, FAMILY_MEMBER, OTHER
+ "confidence": 3.14, # The model's confidence in this feature annotation. A number between 0 and 1.
+ "value": "A String", # The value of this feature annotation. Its range depends on the type of the feature.
+ },
+ "temporalAssessment": { # A feature of an entity mention. # How this entity mention relates to the subject temporally. Its value is one of: CURRENT, CLINICAL_HISTORY, FAMILY_HISTORY, UPCOMING, ALLERGY
+ "confidence": 3.14, # The model's confidence in this feature annotation. A number between 0 and 1.
+ "value": "A String", # The value of this feature annotation. Its range depends on the type of the feature.
+ },
+ "text": { # A span of text in the provided document. # text is the location of the entity mention in the document.
+ "beginOffset": 42, # The unicode codepoint index of the beginning of this span.
+ "content": "A String", # The original text contained in this span.
+ },
+ "type": "A String", # 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.
+ },
+ ],
+ "relationships": [ # relationships contains all the binary relationships that were identified between entity mentions within the provided document.
+ { # Defines directed relationship from one entity mention to another.
+ "confidence": 3.14, # The model's confidence in this annotation. A number between 0 and 1.
+ "objectId": "A String", # object_id is the id of the object entity mention.
+ "subjectId": "A String", # subject_id is the id of the subject entity mention.
+ },
+ ],
+}</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="close">close()</code>
+ <pre>Close httplib2 connections.</pre>
+</div>
+
+</body></html>
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