Detect Entities V2
comprehendmedical_detect_entities_v2 | R Documentation |
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¶
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¶
Arguments¶
Text
[required] A UTF-8 string containing the clinical content being examined for entities.
Value¶
A list with the following syntax:
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"|"BEHAVIORAL_ENVIRONMENTAL_SOCIAL",
Type = "NAME"|"DX_NAME"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"GENERIC_NAME"|"BRAND_NAME"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_NAME"|"TEST_VALUE"|"TEST_UNITS"|"TEST_UNIT"|"PROCEDURE_NAME"|"TREATMENT_NAME"|"DATE"|"AGE"|"CONTACT_POINT"|"PHONE_OR_FAX"|"EMAIL"|"IDENTIFIER"|"ID"|"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"|"AMOUNT"|"GENDER"|"RACE_ETHNICITY"|"ALLERGIES"|"TOBACCO_USE"|"ALCOHOL_CONSUMPTION"|"REC_DRUG_USE",
Traits = list(
list(
Name = "SIGN"|"SYMPTOM"|"DIAGNOSIS"|"NEGATION"|"PERTAINS_TO_FAMILY"|"HYPOTHETICAL"|"LOW_CONFIDENCE"|"PAST_HISTORY"|"FUTURE",
Score = 123.0
)
),
Attributes = list(
list(
Type = "NAME"|"DX_NAME"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"GENERIC_NAME"|"BRAND_NAME"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_NAME"|"TEST_VALUE"|"TEST_UNITS"|"TEST_UNIT"|"PROCEDURE_NAME"|"TREATMENT_NAME"|"DATE"|"AGE"|"CONTACT_POINT"|"PHONE_OR_FAX"|"EMAIL"|"IDENTIFIER"|"ID"|"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"|"AMOUNT"|"GENDER"|"RACE_ETHNICITY"|"ALLERGIES"|"TOBACCO_USE"|"ALCOHOL_CONSUMPTION"|"REC_DRUG_USE",
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"|"TEST_UNIT"|"DIRECTION"|"SYSTEM_ORGAN_SITE"|"AMOUNT"|"USAGE"|"QUALITY",
Id = 123,
BeginOffset = 123,
EndOffset = 123,
Text = "string",
Category = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION"|"BEHAVIORAL_ENVIRONMENTAL_SOCIAL",
Traits = list(
list(
Name = "SIGN"|"SYMPTOM"|"DIAGNOSIS"|"NEGATION"|"PERTAINS_TO_FAMILY"|"HYPOTHETICAL"|"LOW_CONFIDENCE"|"PAST_HISTORY"|"FUTURE",
Score = 123.0
)
)
)
)
)
),
UnmappedAttributes = list(
list(
Type = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION"|"BEHAVIORAL_ENVIRONMENTAL_SOCIAL",
Attribute = list(
Type = "NAME"|"DX_NAME"|"DOSAGE"|"ROUTE_OR_MODE"|"FORM"|"FREQUENCY"|"DURATION"|"GENERIC_NAME"|"BRAND_NAME"|"STRENGTH"|"RATE"|"ACUITY"|"TEST_NAME"|"TEST_VALUE"|"TEST_UNITS"|"TEST_UNIT"|"PROCEDURE_NAME"|"TREATMENT_NAME"|"DATE"|"AGE"|"CONTACT_POINT"|"PHONE_OR_FAX"|"EMAIL"|"IDENTIFIER"|"ID"|"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"|"AMOUNT"|"GENDER"|"RACE_ETHNICITY"|"ALLERGIES"|"TOBACCO_USE"|"ALCOHOL_CONSUMPTION"|"REC_DRUG_USE",
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"|"TEST_UNIT"|"DIRECTION"|"SYSTEM_ORGAN_SITE"|"AMOUNT"|"USAGE"|"QUALITY",
Id = 123,
BeginOffset = 123,
EndOffset = 123,
Text = "string",
Category = "MEDICATION"|"MEDICAL_CONDITION"|"PROTECTED_HEALTH_INFORMATION"|"TEST_TREATMENT_PROCEDURE"|"ANATOMY"|"TIME_EXPRESSION"|"BEHAVIORAL_ENVIRONMENTAL_SOCIAL",
Traits = list(
list(
Name = "SIGN"|"SYMPTOM"|"DIAGNOSIS"|"NEGATION"|"PERTAINS_TO_FAMILY"|"HYPOTHETICAL"|"LOW_CONFIDENCE"|"PAST_HISTORY"|"FUTURE",
Score = 123.0
)
)
)
)
),
PaginationToken = "string",
ModelVersion = "string"
)