comprehendmedical_detect_entities_v2: Inspects the clinical text for a variety of medical entities...

Description Usage Arguments Value Request syntax

View source: R/comprehendmedical_operations.R

Description

Inspects the clinical text for a variety of medical entities and returns specific information about them such as entity category, location, and confidence score on that information. Amazon Comprehend Medical only detects medical entities in English language texts.

The detect_entities_v2 operation replaces the detect_entities operation. This new action uses a different model for determining the entities in your medical text and changes the way that some entities are returned in the output. You should use the detect_entities_v2 operation in all new applications.

The detect_entities_v2 operation returns the Acuity and Direction entities as attributes instead of types.

Usage

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Arguments

Text

[required] A UTF-8 string containing the clinical content being examined for entities. Each string must contain fewer than 20,000 bytes of characters.

Value

A list with the following syntax:

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list(
  Entities = list(
    list(
      Id = 123,
      BeginOffset = 123,
      EndOffset = 123,
      Score = 123.0,
      Text = "string",
      Category = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION",
      Type = "NAME"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"GENERIC_NAME"|"BRAND_NAME"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_NAME"|"TEST_VALUE"|"TEST_UNITS"|"PROCEDURE_NAME"|"TREATMENT_NAME"|"DATE"|"AGE"|"CONTACT_POINT"|"EMAIL"|"IDENTIFIER"|"URL"|"ADDRESS"|"PROFESSION"|"SYSTEM_ORGAN_SITE"|"DIRECTION"|"QUALITY"|"QUANTITY"|"TIME_EXPRESSION"|"TIME_TO_MEDICATION_NAME"|"TIME_TO_DX_NAME"|"TIME_TO_TEST_NAME"|"TIME_TO_PROCEDURE_NAME"|"TIME_TO_TREATMENT_NAME",
      Traits = list(
        list(
          Name = "SIGN"|"SYMPTOM"|"DIAGNOSIS"|"NEGATION",
          Score = 123.0
        )
      ),
      Attributes = list(
        list(
          Type = "NAME"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"GENERIC_NAME"|"BRAND_NAME"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_NAME"|"TEST_VALUE"|"TEST_UNITS"|"PROCEDURE_NAME"|"TREATMENT_NAME"|"DATE"|"AGE"|"CONTACT_POINT"|"EMAIL"|"IDENTIFIER"|"URL"|"ADDRESS"|"PROFESSION"|"SYSTEM_ORGAN_SITE"|"DIRECTION"|"QUALITY"|"QUANTITY"|"TIME_EXPRESSION"|"TIME_TO_MEDICATION_NAME"|"TIME_TO_DX_NAME"|"TIME_TO_TEST_NAME"|"TIME_TO_PROCEDURE_NAME"|"TIME_TO_TREATMENT_NAME",
          Score = 123.0,
          RelationshipScore = 123.0,
          RelationshipType = "EVERY"|"WITH_DOSAGE"|"ADMINISTERED_VIA"|"FOR"|"NEGATIVE"|"OVERLAP"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_VALUE"|"TEST_UNITS"|"DIRECTION"|"SYSTEM_ORGAN_SITE",
          Id = 123,
          BeginOffset = 123,
          EndOffset = 123,
          Text = "string",
          Category = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION",
          Traits = list(
            list(
              Name = "SIGN"|"SYMPTOM"|"DIAGNOSIS"|"NEGATION",
              Score = 123.0
            )
          )
        )
      )
    )
  ),
  UnmappedAttributes = list(
    list(
      Type = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION",
      Attribute = list(
        Type = "NAME"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"GENERIC_NAME"|"BRAND_NAME"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_NAME"|"TEST_VALUE"|"TEST_UNITS"|"PROCEDURE_NAME"|"TREATMENT_NAME"|"DATE"|"AGE"|"CONTACT_POINT"|"EMAIL"|"IDENTIFIER"|"URL"|"ADDRESS"|"PROFESSION"|"SYSTEM_ORGAN_SITE"|"DIRECTION"|"QUALITY"|"QUANTITY"|"TIME_EXPRESSION"|"TIME_TO_MEDICATION_NAME"|"TIME_TO_DX_NAME"|"TIME_TO_TEST_NAME"|"TIME_TO_PROCEDURE_NAME"|"TIME_TO_TREATMENT_NAME",
        Score = 123.0,
        RelationshipScore = 123.0,
        RelationshipType = "EVERY"|"WITH_DOSAGE"|"ADMINISTERED_VIA"|"FOR"|"NEGATIVE"|"OVERLAP"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_VALUE"|"TEST_UNITS"|"DIRECTION"|"SYSTEM_ORGAN_SITE",
        Id = 123,
        BeginOffset = 123,
        EndOffset = 123,
        Text = "string",
        Category = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION",
        Traits = list(
          list(
            Name = "SIGN"|"SYMPTOM"|"DIAGNOSIS"|"NEGATION",
            Score = 123.0
          )
        )
      )
    )
  ),
  PaginationToken = "string",
  ModelVersion = "string"
)

Request syntax

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svc$detect_entities_v2(
  Text = "string"
)

paws.machine.learning documentation built on Aug. 23, 2021, 9:14 a.m.