An extracted segment of the text that is an attribute of an entity, or otherwise related to an entity, such as the dosage of a medication taken. It contains information about the attribute such as id, begin and end offset within the input text, and the segment of the input text.

The number of characters in the input text to be analyzed.

Provides information for filtering a list of detection jobs.

Provides information about a detection job.

Provides information about an extracted medical entity.

The detected attributes that relate to an entity. This includes an extracted segment of the text that is an attribute of an entity, or otherwise related to an entity. InferICD10CM detects the following attributes: Direction, System, Organ or Site, and Acuity.

The ICD-10-CM concepts that the entity could refer to, along with a score indicating the likelihood of the match.

The collection of medical entities extracted from the input text and their associated information. For each entity, the response provides the entity text, the entity category, where the entity text begins and ends, and the level of confidence that Amazon Comprehend Medical has in the detection and analysis. Attributes and traits of the entity are also returned.

Contextual information for the entity. The traits recognized by InferICD10CM are DIAGNOSIS, SIGN, SYMPTOM, and NEGATION.

The input properties for an entities detection job. This includes the name of the S3 bucket and the path to the files to be analyzed.

The output properties for a detection job.

The extracted attributes that relate to this entity. The attributes recognized by InferRxNorm are DOSAGE, DURATION, FORM, FREQUENCY, RATE, ROUTE_OR_MODE.

The RxNorm concept that the entity could refer to, along with a score indicating the likelihood of the match.

The collection of medical entities extracted from the input text and their associated information. For each entity, the response provides the entity text, the entity category, where the entity text begins and ends, and the level of confidence that Amazon Comprehend Medical has in the detection and analysis. Attributes and traits of the entity are also returned.

The contextual information for the entity. InferRxNorm recognizes the trait NEGATION, which is any indication that the patient is not taking a medication.

The extracted attributes that relate to an entity. An extracted segment of the text that is an attribute of an entity, or otherwise related to an entity, such as the dosage of a medication taken.

The SNOMED-CT concepts that the entity could refer to, along with a score indicating the likelihood of the match.

The information about the revision of the SNOMED-CT ontology in the response. Specifically, the details include the SNOMED-CT edition, language, and version date.

The collection of medical entities extracted from the input text and their associated information. For each entity, the response provides the entity text, the entity category, where the entity text begins and ends, and the level of confidence that Comprehend Medical has in the detection and analysis. Attributes and traits of the entity are also returned.

Contextual information for an entity.

Provides contextual information about the extracted entity.

An attribute that was extracted, but Comprehend Medical; was unable to relate to an entity.