| Bu Sun Kim | 673ec5c | 2020-11-16 11:05:03 -0700 | [diff] [blame] | 1 | <html><body> |
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| 75 | <h1><a href="healthcare_v1beta1.html">Cloud Healthcare API</a> . <a href="healthcare_v1beta1.projects.html">projects</a> . <a href="healthcare_v1beta1.projects.locations.html">locations</a> . <a href="healthcare_v1beta1.projects.locations.services.html">services</a> . <a href="healthcare_v1beta1.projects.locations.services.nlp.html">nlp</a></h1> |
| 76 | <h2>Instance Methods</h2> |
| 77 | <p class="toc_element"> |
| 78 | <code><a href="#analyzeEntities">analyzeEntities(nlpService, body=None, x__xgafv=None)</a></code></p> |
| 79 | <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> |
| 80 | <p class="toc_element"> |
| 81 | <code><a href="#close">close()</a></code></p> |
| 82 | <p class="firstline">Close httplib2 connections.</p> |
| 83 | <h3>Method Details</h3> |
| 84 | <div class="method"> |
| 85 | <code class="details" id="analyzeEntities">analyzeEntities(nlpService, body=None, x__xgafv=None)</code> |
| 86 | <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. |
| 87 | |
| 88 | Args: |
| 89 | nlpService: string, The resource name of the service of the form: "projects/{project_id}/locations/{location_id}/services/nlp". (required) |
| 90 | body: object, The request body. |
| 91 | The object takes the form of: |
| 92 | |
| 93 | { # The request to analyze healthcare entities in a document. |
| 94 | "documentContent": "A String", # document_content is a document to be annotated. |
| 95 | } |
| 96 | |
| 97 | x__xgafv: string, V1 error format. |
| 98 | Allowed values |
| 99 | 1 - v1 error format |
| 100 | 2 - v2 error format |
| 101 | |
| 102 | Returns: |
| 103 | An object of the form: |
| 104 | |
| 105 | { # Includes recognized entity mentions and relationships between them. |
| Yoshi Automation Bot | 0d561ef | 2020-11-25 07:50:41 -0800 | [diff] [blame^] | 106 | "relationships": [ # relationships contains all the binary relationships that were identified between entity mentions within the provided document. |
| 107 | { # Defines directed relationship from one entity mention to another. |
| 108 | "confidence": 3.14, # The model's confidence in this annotation. A number between 0 and 1. |
| 109 | "subjectId": "A String", # subject_id is the id of the subject entity mention. |
| 110 | "objectId": "A String", # object_id is the id of the object entity mention. |
| Bu Sun Kim | 673ec5c | 2020-11-16 11:05:03 -0700 | [diff] [blame] | 111 | }, |
| 112 | ], |
| 113 | "entityMentions": [ # entity_mentions contains all the annotated medical entities that were were mentioned in the provided document. |
| 114 | { # An entity mention in the document. |
| Bu Sun Kim | 673ec5c | 2020-11-16 11:05:03 -0700 | [diff] [blame] | 115 | "linkedEntities": [ # linked_entities are candidate ontological concepts that this entity mention may refer to. They are sorted by decreasing confidence.it |
| 116 | { # EntityMentions can be linked to multiple entities using a LinkedEntity message lets us add other fields, e.g. confidence. |
| 117 | "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. |
| 118 | }, |
| 119 | ], |
| Yoshi Automation Bot | 0d561ef | 2020-11-25 07:50:41 -0800 | [diff] [blame^] | 120 | "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. |
| Yoshi Automation Bot | c2228be | 2020-11-24 15:48:03 -0800 | [diff] [blame] | 121 | "mentionId": "A String", # mention_id uniquely identifies each entity mention in a single response. |
| Yoshi Automation Bot | 0d561ef | 2020-11-25 07:50:41 -0800 | [diff] [blame^] | 122 | "subject": { # A feature of an entity mention. # The subject this entity mention relates to. Its value is one of: PATIENT, FAMILY_MEMBER, OTHER |
| 123 | "value": "A String", # The value of this feature annotation. Its range depends on the type of the feature. |
| 124 | "confidence": 3.14, # The model's confidence in this feature annotation. A number between 0 and 1. |
| 125 | }, |
| 126 | "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 |
| 127 | "value": "A String", # The value of this feature annotation. Its range depends on the type of the feature. |
| 128 | "confidence": 3.14, # The model's confidence in this feature annotation. A number between 0 and 1. |
| 129 | }, |
| 130 | "confidence": 3.14, # The model's confidence in this entity mention annotation. A number between 0 and 1. |
| 131 | "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 |
| 132 | "value": "A String", # The value of this feature annotation. Its range depends on the type of the feature. |
| 133 | "confidence": 3.14, # The model's confidence in this feature annotation. A number between 0 and 1. |
| 134 | }, |
| Bu Sun Kim | 673ec5c | 2020-11-16 11:05:03 -0700 | [diff] [blame] | 135 | "text": { # A span of text in the provided document. # text is the location of the entity mention in the document. |
| 136 | "content": "A String", # The original text contained in this span. |
| 137 | "beginOffset": 42, # The unicode codepoint index of the beginning of this span. |
| 138 | }, |
| Yoshi Automation Bot | c2228be | 2020-11-24 15:48:03 -0800 | [diff] [blame] | 139 | }, |
| 140 | ], |
| Yoshi Automation Bot | 0d561ef | 2020-11-25 07:50:41 -0800 | [diff] [blame^] | 141 | "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. |
| 142 | { # The candidate entities that an entity mention could link to. |
| 143 | "entityId": "A String", # entity_id is a first class field entity_id uniquely identifies this concept and its meta-vocabulary. For example, "UMLS/C0000970". |
| 144 | "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. |
| 145 | "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". |
| 146 | "A String", |
| 147 | ], |
| Bu Sun Kim | 673ec5c | 2020-11-16 11:05:03 -0700 | [diff] [blame] | 148 | }, |
| 149 | ], |
| 150 | }</pre> |
| 151 | </div> |
| 152 | |
| 153 | <div class="method"> |
| 154 | <code class="details" id="close">close()</code> |
| 155 | <pre>Close httplib2 connections.</pre> |
| 156 | </div> |
| 157 | |
| 158 | </body></html> |