ComprehendMedical

Table of Contents

Client

class ComprehendMedical.Client

A low-level client representing AWS Comprehend Medical (ComprehendMedical):

client = session.create_client('comprehendmedical')

These are the available methods:

can_paginate(operation_name)

Check if an operation can be paginated.

Parameters
operation_name (string) -- The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator("create_foo").
Returns
True if the operation can be paginated, False otherwise.
describe_entities_detection_v2_job(**kwargs)

Gets the properties associated with a medical entities detection job. Use this operation to get the status of a detection job.

See also: AWS API Documentation

Request Syntax

response = client.describe_entities_detection_v2_job(
    JobId='string'
)
Parameters
JobId (string) --

[REQUIRED]

The identifier that Amazon Comprehend Medical generated for the job. The StartEntitiesDetectionV2Job operation returns this identifier in its response.

Return type
dict
Returns
Response Syntax
{
    'ComprehendMedicalAsyncJobProperties': {
        'JobId': 'string',
        'JobName': 'string',
        'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
        'Message': 'string',
        'SubmitTime': datetime(2015, 1, 1),
        'EndTime': datetime(2015, 1, 1),
        'ExpirationTime': datetime(2015, 1, 1),
        'InputDataConfig': {
            'S3Bucket': 'string',
            'S3Key': 'string'
        },
        'OutputDataConfig': {
            'S3Bucket': 'string',
            'S3Key': 'string'
        },
        'LanguageCode': 'en',
        'DataAccessRoleArn': 'string',
        'ManifestFilePath': 'string',
        'KMSKey': 'string',
        'ModelVersion': 'string'
    }
}

Response Structure

  • (dict) --
    • ComprehendMedicalAsyncJobProperties (dict) --

      An object that contains the properties associated with a detection job.

      • JobId (string) --

        The identifier assigned to the detection job.

      • JobName (string) --

        The name that you assigned to the detection job.

      • JobStatus (string) --

        The current status of the detection job. If the status is FAILED , the Message field shows the reason for the failure.

      • Message (string) --

        A description of the status of a job.

      • SubmitTime (datetime) --

        The time that the detection job was submitted for processing.

      • EndTime (datetime) --

        The time that the detection job completed.

      • ExpirationTime (datetime) --

        The date and time that job metadata is deleted from the server. Output files in your S3 bucket will not be deleted. After the metadata is deleted, the job will no longer appear in the results of the ListEntitiesDetectionV2Job or the ListPHIDetectionJobs operation.

      • InputDataConfig (dict) --

        The input data configuration that you supplied when you created the detection job.

        • S3Bucket (string) --

          The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

          Each file in the document collection must be less than 40 KB. You can store a maximum of 30 GB in the bucket.

        • S3Key (string) --

          The path to the input data files in the S3 bucket.

      • OutputDataConfig (dict) --

        The output data configuration that you supplied when you created the detection job.

        • S3Bucket (string) --

          When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output.

        • S3Key (string) --

          The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

      • LanguageCode (string) --

        The language code of the input documents.

      • DataAccessRoleArn (string) --

        The Amazon Resource Name (ARN) that gives Amazon Comprehend Medical read access to your input data.

      • ManifestFilePath (string) --

        The path to the file that describes the results of a batch job.

      • KMSKey (string) --

        The AWS Key Management Service key, if any, used to encrypt the output files.

      • ModelVersion (string) --

        The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

describe_phi_detection_job(**kwargs)

Gets the properties associated with a protected health information (PHI) detection job. Use this operation to get the status of a detection job.

See also: AWS API Documentation

Request Syntax

response = client.describe_phi_detection_job(
    JobId='string'
)
Parameters
JobId (string) --

[REQUIRED]

The identifier that Amazon Comprehend Medical generated for the job. The StartPHIDetectionJob operation returns this identifier in its response.

Return type
dict
Returns
Response Syntax
{
    'ComprehendMedicalAsyncJobProperties': {
        'JobId': 'string',
        'JobName': 'string',
        'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
        'Message': 'string',
        'SubmitTime': datetime(2015, 1, 1),
        'EndTime': datetime(2015, 1, 1),
        'ExpirationTime': datetime(2015, 1, 1),
        'InputDataConfig': {
            'S3Bucket': 'string',
            'S3Key': 'string'
        },
        'OutputDataConfig': {
            'S3Bucket': 'string',
            'S3Key': 'string'
        },
        'LanguageCode': 'en',
        'DataAccessRoleArn': 'string',
        'ManifestFilePath': 'string',
        'KMSKey': 'string',
        'ModelVersion': 'string'
    }
}

Response Structure

  • (dict) --
    • ComprehendMedicalAsyncJobProperties (dict) --

      An object that contains the properties associated with a detection job.

      • JobId (string) --

        The identifier assigned to the detection job.

      • JobName (string) --

        The name that you assigned to the detection job.

      • JobStatus (string) --

        The current status of the detection job. If the status is FAILED , the Message field shows the reason for the failure.

      • Message (string) --

        A description of the status of a job.

      • SubmitTime (datetime) --

        The time that the detection job was submitted for processing.

      • EndTime (datetime) --

        The time that the detection job completed.

      • ExpirationTime (datetime) --

        The date and time that job metadata is deleted from the server. Output files in your S3 bucket will not be deleted. After the metadata is deleted, the job will no longer appear in the results of the ListEntitiesDetectionV2Job or the ListPHIDetectionJobs operation.

      • InputDataConfig (dict) --

        The input data configuration that you supplied when you created the detection job.

        • S3Bucket (string) --

          The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

          Each file in the document collection must be less than 40 KB. You can store a maximum of 30 GB in the bucket.

        • S3Key (string) --

          The path to the input data files in the S3 bucket.

      • OutputDataConfig (dict) --

        The output data configuration that you supplied when you created the detection job.

        • S3Bucket (string) --

          When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output.

        • S3Key (string) --

          The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

      • LanguageCode (string) --

        The language code of the input documents.

      • DataAccessRoleArn (string) --

        The Amazon Resource Name (ARN) that gives Amazon Comprehend Medical read access to your input data.

      • ManifestFilePath (string) --

        The path to the file that describes the results of a batch job.

      • KMSKey (string) --

        The AWS Key Management Service key, if any, used to encrypt the output files.

      • ModelVersion (string) --

        The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

detect_entities(**kwargs)

The DetectEntities operation is deprecated. You should use the DetectEntitiesV2 operation instead.

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 .

Danger

This operation is deprecated and may not function as expected. This operation should not be used going forward and is only kept for the purpose of backwards compatiblity.

See also: AWS API Documentation

Request Syntax

response = client.detect_entities(
    Text='string'
)
Parameters
Text (string) --

[REQUIRED]

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

Return type
dict
Returns
Response Syntax
{
    'Entities': [
        {
            'Id': 123,
            'BeginOffset': 123,
            'EndOffset': 123,
            'Score': ...,
            'Text': 'string',
            'Category': 'MEDICATION'|'MEDICAL_CONDITION'|'PROTECTED_HEALTH_INFORMATION'|'TEST_TREATMENT_PROCEDURE'|'ANATOMY',
            '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',
            'Traits': [
                {
                    'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                    'Score': ...
                },
            ],
            'Attributes': [
                {
                    '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',
                    'Score': ...,
                    'RelationshipScore': ...,
                    'Id': 123,
                    'BeginOffset': 123,
                    'EndOffset': 123,
                    'Text': 'string',
                    'Traits': [
                        {
                            'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                            'Score': ...
                        },
                    ]
                },
            ]
        },
    ],
    'UnmappedAttributes': [
        {
            'Type': 'MEDICATION'|'MEDICAL_CONDITION'|'PROTECTED_HEALTH_INFORMATION'|'TEST_TREATMENT_PROCEDURE'|'ANATOMY',
            'Attribute': {
                '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',
                'Score': ...,
                'RelationshipScore': ...,
                'Id': 123,
                'BeginOffset': 123,
                'EndOffset': 123,
                'Text': 'string',
                'Traits': [
                    {
                        'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                        'Score': ...
                    },
                ]
            }
        },
    ],
    'PaginationToken': 'string',
    'ModelVersion': 'string'
}

Response Structure

  • (dict) --
    • Entities (list) --

      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.

      • (dict) --

        Provides information about an extracted medical entity.

        • Id (integer) --

          The numeric identifier for the entity. This is a monotonically increasing id unique within this response rather than a global unique identifier.

        • BeginOffset (integer) --

          The 0-based character offset in the input text that shows where the entity begins. The offset returns the UTF-8 code point in the string.

        • EndOffset (integer) --

          The 0-based character offset in the input text that shows where the entity ends. The offset returns the UTF-8 code point in the string.

        • Score (float) --

          The level of confidence that Amazon Comprehend Medical has in the accuracy of the detection.

        • Text (string) --

          The segment of input text extracted as this entity.

        • Category (string) --

          The category of the entity.

        • Type (string) --

          Describes the specific type of entity with category of entities.

        • Traits (list) --

          Contextual information for the entity

          • (dict) --

            Provides contextual information about the extracted entity.

            • Name (string) --

              Provides a name or contextual description about the trait.

            • Score (float) --

              The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

        • Attributes (list) --

          The extracted attributes that relate to this entity.

          • (dict) --

            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.

            • Type (string) --

              The type of attribute.

            • Score (float) --

              The level of confidence that Amazon Comprehend Medical has that the segment of text is correctly recognized as an attribute.

            • RelationshipScore (float) --

              The level of confidence that Amazon Comprehend Medical has that this attribute is correctly related to this entity.

            • Id (integer) --

              The numeric identifier for this attribute. This is a monotonically increasing id unique within this response rather than a global unique identifier.

            • BeginOffset (integer) --

              The 0-based character offset in the input text that shows where the attribute begins. The offset returns the UTF-8 code point in the string.

            • EndOffset (integer) --

              The 0-based character offset in the input text that shows where the attribute ends. The offset returns the UTF-8 code point in the string.

            • Text (string) --

              The segment of input text extracted as this attribute.

            • Traits (list) --

              Contextual information for this attribute.

              • (dict) --

                Provides contextual information about the extracted entity.

                • Name (string) --

                  Provides a name or contextual description about the trait.

                • Score (float) --

                  The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

    • UnmappedAttributes (list) --

      Attributes extracted from the input text that we were unable to relate to an entity.

      • (dict) --

        An attribute that we extracted, but were unable to relate to an entity.

        • Type (string) --

          The type of the attribute, could be one of the following values: "MEDICATION", "MEDICAL_CONDITION", "ANATOMY", "TEST_AND_TREATMENT_PROCEDURE" or "PROTECTED_HEALTH_INFORMATION".

        • Attribute (dict) --

          The specific attribute that has been extracted but not mapped to an entity.

          • Type (string) --

            The type of attribute.

          • Score (float) --

            The level of confidence that Amazon Comprehend Medical has that the segment of text is correctly recognized as an attribute.

          • RelationshipScore (float) --

            The level of confidence that Amazon Comprehend Medical has that this attribute is correctly related to this entity.

          • Id (integer) --

            The numeric identifier for this attribute. This is a monotonically increasing id unique within this response rather than a global unique identifier.

          • BeginOffset (integer) --

            The 0-based character offset in the input text that shows where the attribute begins. The offset returns the UTF-8 code point in the string.

          • EndOffset (integer) --

            The 0-based character offset in the input text that shows where the attribute ends. The offset returns the UTF-8 code point in the string.

          • Text (string) --

            The segment of input text extracted as this attribute.

          • Traits (list) --

            Contextual information for this attribute.

            • (dict) --

              Provides contextual information about the extracted entity.

              • Name (string) --

                Provides a name or contextual description about the trait.

              • Score (float) --

                The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

    • PaginationToken (string) --

      If the result of the previous request to DetectEntities was truncated, include the PaginationToken to fetch the next page of entities.

    • ModelVersion (string) --

      The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

detect_entities_v2(**kwargs)

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.

The DetectEntitiesV2 operation replaces the DetectEntities 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 DetectEntitiesV2 operation in all new applications.

The DetectEntitiesV2 operation returns the Acuity and Direction entities as attributes instead of types. It does not return the Quality or Quantity entities.

See also: AWS API Documentation

Request Syntax

response = client.detect_entities_v2(
    Text='string'
)
Parameters
Text (string) --

[REQUIRED]

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

Return type
dict
Returns
Response Syntax
{
    'Entities': [
        {
            'Id': 123,
            'BeginOffset': 123,
            'EndOffset': 123,
            'Score': ...,
            'Text': 'string',
            'Category': 'MEDICATION'|'MEDICAL_CONDITION'|'PROTECTED_HEALTH_INFORMATION'|'TEST_TREATMENT_PROCEDURE'|'ANATOMY',
            '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',
            'Traits': [
                {
                    'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                    'Score': ...
                },
            ],
            'Attributes': [
                {
                    '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',
                    'Score': ...,
                    'RelationshipScore': ...,
                    'Id': 123,
                    'BeginOffset': 123,
                    'EndOffset': 123,
                    'Text': 'string',
                    'Traits': [
                        {
                            'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                            'Score': ...
                        },
                    ]
                },
            ]
        },
    ],
    'UnmappedAttributes': [
        {
            'Type': 'MEDICATION'|'MEDICAL_CONDITION'|'PROTECTED_HEALTH_INFORMATION'|'TEST_TREATMENT_PROCEDURE'|'ANATOMY',
            'Attribute': {
                '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',
                'Score': ...,
                'RelationshipScore': ...,
                'Id': 123,
                'BeginOffset': 123,
                'EndOffset': 123,
                'Text': 'string',
                'Traits': [
                    {
                        'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                        'Score': ...
                    },
                ]
            }
        },
    ],
    'PaginationToken': 'string',
    'ModelVersion': 'string'
}

Response Structure

  • (dict) --
    • Entities (list) --

      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 in the detection and analysis. Attributes and traits of the entity are also returned.

      • (dict) --

        Provides information about an extracted medical entity.

        • Id (integer) --

          The numeric identifier for the entity. This is a monotonically increasing id unique within this response rather than a global unique identifier.

        • BeginOffset (integer) --

          The 0-based character offset in the input text that shows where the entity begins. The offset returns the UTF-8 code point in the string.

        • EndOffset (integer) --

          The 0-based character offset in the input text that shows where the entity ends. The offset returns the UTF-8 code point in the string.

        • Score (float) --

          The level of confidence that Amazon Comprehend Medical has in the accuracy of the detection.

        • Text (string) --

          The segment of input text extracted as this entity.

        • Category (string) --

          The category of the entity.

        • Type (string) --

          Describes the specific type of entity with category of entities.

        • Traits (list) --

          Contextual information for the entity

          • (dict) --

            Provides contextual information about the extracted entity.

            • Name (string) --

              Provides a name or contextual description about the trait.

            • Score (float) --

              The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

        • Attributes (list) --

          The extracted attributes that relate to this entity.

          • (dict) --

            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.

            • Type (string) --

              The type of attribute.

            • Score (float) --

              The level of confidence that Amazon Comprehend Medical has that the segment of text is correctly recognized as an attribute.

            • RelationshipScore (float) --

              The level of confidence that Amazon Comprehend Medical has that this attribute is correctly related to this entity.

            • Id (integer) --

              The numeric identifier for this attribute. This is a monotonically increasing id unique within this response rather than a global unique identifier.

            • BeginOffset (integer) --

              The 0-based character offset in the input text that shows where the attribute begins. The offset returns the UTF-8 code point in the string.

            • EndOffset (integer) --

              The 0-based character offset in the input text that shows where the attribute ends. The offset returns the UTF-8 code point in the string.

            • Text (string) --

              The segment of input text extracted as this attribute.

            • Traits (list) --

              Contextual information for this attribute.

              • (dict) --

                Provides contextual information about the extracted entity.

                • Name (string) --

                  Provides a name or contextual description about the trait.

                • Score (float) --

                  The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

    • UnmappedAttributes (list) --

      Attributes extracted from the input text that couldn't be related to an entity.

      • (dict) --

        An attribute that we extracted, but were unable to relate to an entity.

        • Type (string) --

          The type of the attribute, could be one of the following values: "MEDICATION", "MEDICAL_CONDITION", "ANATOMY", "TEST_AND_TREATMENT_PROCEDURE" or "PROTECTED_HEALTH_INFORMATION".

        • Attribute (dict) --

          The specific attribute that has been extracted but not mapped to an entity.

          • Type (string) --

            The type of attribute.

          • Score (float) --

            The level of confidence that Amazon Comprehend Medical has that the segment of text is correctly recognized as an attribute.

          • RelationshipScore (float) --

            The level of confidence that Amazon Comprehend Medical has that this attribute is correctly related to this entity.

          • Id (integer) --

            The numeric identifier for this attribute. This is a monotonically increasing id unique within this response rather than a global unique identifier.

          • BeginOffset (integer) --

            The 0-based character offset in the input text that shows where the attribute begins. The offset returns the UTF-8 code point in the string.

          • EndOffset (integer) --

            The 0-based character offset in the input text that shows where the attribute ends. The offset returns the UTF-8 code point in the string.

          • Text (string) --

            The segment of input text extracted as this attribute.

          • Traits (list) --

            Contextual information for this attribute.

            • (dict) --

              Provides contextual information about the extracted entity.

              • Name (string) --

                Provides a name or contextual description about the trait.

              • Score (float) --

                The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

    • PaginationToken (string) --

      If the result to the DetectEntitiesV2 operation was truncated, include the PaginationToken to fetch the next page of entities.

    • ModelVersion (string) --

      The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

detect_phi(**kwargs)

Inspects the clinical text for protected health information (PHI) entities and entity category, location, and confidence score on that information.

See also: AWS API Documentation

Request Syntax

response = client.detect_phi(
    Text='string'
)
Parameters
Text (string) --

[REQUIRED]

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

Return type
dict
Returns
Response Syntax
{
    'Entities': [
        {
            'Id': 123,
            'BeginOffset': 123,
            'EndOffset': 123,
            'Score': ...,
            'Text': 'string',
            'Category': 'MEDICATION'|'MEDICAL_CONDITION'|'PROTECTED_HEALTH_INFORMATION'|'TEST_TREATMENT_PROCEDURE'|'ANATOMY',
            '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',
            'Traits': [
                {
                    'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                    'Score': ...
                },
            ],
            'Attributes': [
                {
                    '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',
                    'Score': ...,
                    'RelationshipScore': ...,
                    'Id': 123,
                    'BeginOffset': 123,
                    'EndOffset': 123,
                    'Text': 'string',
                    'Traits': [
                        {
                            'Name': 'SIGN'|'SYMPTOM'|'DIAGNOSIS'|'NEGATION',
                            'Score': ...
                        },
                    ]
                },
            ]
        },
    ],
    'PaginationToken': 'string',
    'ModelVersion': 'string'
}

Response Structure

  • (dict) --
    • Entities (list) --

      The collection of PHI 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 its detection.

      • (dict) --

        Provides information about an extracted medical entity.

        • Id (integer) --

          The numeric identifier for the entity. This is a monotonically increasing id unique within this response rather than a global unique identifier.

        • BeginOffset (integer) --

          The 0-based character offset in the input text that shows where the entity begins. The offset returns the UTF-8 code point in the string.

        • EndOffset (integer) --

          The 0-based character offset in the input text that shows where the entity ends. The offset returns the UTF-8 code point in the string.

        • Score (float) --

          The level of confidence that Amazon Comprehend Medical has in the accuracy of the detection.

        • Text (string) --

          The segment of input text extracted as this entity.

        • Category (string) --

          The category of the entity.

        • Type (string) --

          Describes the specific type of entity with category of entities.

        • Traits (list) --

          Contextual information for the entity

          • (dict) --

            Provides contextual information about the extracted entity.

            • Name (string) --

              Provides a name or contextual description about the trait.

            • Score (float) --

              The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

        • Attributes (list) --

          The extracted attributes that relate to this entity.

          • (dict) --

            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.

            • Type (string) --

              The type of attribute.

            • Score (float) --

              The level of confidence that Amazon Comprehend Medical has that the segment of text is correctly recognized as an attribute.

            • RelationshipScore (float) --

              The level of confidence that Amazon Comprehend Medical has that this attribute is correctly related to this entity.

            • Id (integer) --

              The numeric identifier for this attribute. This is a monotonically increasing id unique within this response rather than a global unique identifier.

            • BeginOffset (integer) --

              The 0-based character offset in the input text that shows where the attribute begins. The offset returns the UTF-8 code point in the string.

            • EndOffset (integer) --

              The 0-based character offset in the input text that shows where the attribute ends. The offset returns the UTF-8 code point in the string.

            • Text (string) --

              The segment of input text extracted as this attribute.

            • Traits (list) --

              Contextual information for this attribute.

              • (dict) --

                Provides contextual information about the extracted entity.

                • Name (string) --

                  Provides a name or contextual description about the trait.

                • Score (float) --

                  The level of confidence that Amazon Comprehend Medical has in the accuracy of this trait.

    • PaginationToken (string) --

      If the result of the previous request to DetectPHI was truncated, include the PaginationToken to fetch the next page of PHI entities.

    • ModelVersion (string) --

      The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

generate_presigned_url(ClientMethod, Params=None, ExpiresIn=3600, HttpMethod=None)

Generate a presigned url given a client, its method, and arguments

Parameters
  • ClientMethod (string) -- The client method to presign for
  • Params (dict) -- The parameters normally passed to ClientMethod.
  • ExpiresIn (int) -- The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds)
  • HttpMethod (string) -- The http method to use on the generated url. By default, the http method is whatever is used in the method's model.
Returns

The presigned url

get_paginator(operation_name)

Create a paginator for an operation.

Parameters
operation_name (string) -- The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator("create_foo").
Raises OperationNotPageableError
Raised if the operation is not pageable. You can use the client.can_paginate method to check if an operation is pageable.
Return type
L{botocore.paginate.Paginator}
Returns
A paginator object.
get_waiter(waiter_name)

Returns an object that can wait for some condition.

Parameters
waiter_name (str) -- The name of the waiter to get. See the waiters section of the service docs for a list of available waiters.
Returns
The specified waiter object.
Return type
botocore.waiter.Waiter
list_entities_detection_v2_jobs(**kwargs)

Gets a list of medical entity detection jobs that you have submitted.

See also: AWS API Documentation

Request Syntax

response = client.list_entities_detection_v2_jobs(
    Filter={
        'JobName': 'string',
        'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
        'SubmitTimeBefore': datetime(2015, 1, 1),
        'SubmitTimeAfter': datetime(2015, 1, 1)
    },
    NextToken='string',
    MaxResults=123
)
Parameters
  • Filter (dict) --

    Filters the jobs that are returned. You can filter jobs based on their names, status, or the date and time that they were submitted. You can only set one filter at a time.

    • JobName (string) --

      Filters on the name of the job.

    • JobStatus (string) --

      Filters the list of jobs based on job status. Returns only jobs with the specified status.

    • SubmitTimeBefore (datetime) --

      Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in ascending order, oldest to newest.

    • SubmitTimeAfter (datetime) --

      Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in descending order, newest to oldest.

  • NextToken (string) -- Identifies the next page of results to return.
  • MaxResults (integer) -- The maximum number of results to return in each page. The default is 100.
Return type

dict

Returns

Response Syntax

{
    'ComprehendMedicalAsyncJobPropertiesList': [
        {
            'JobId': 'string',
            'JobName': 'string',
            'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
            'Message': 'string',
            'SubmitTime': datetime(2015, 1, 1),
            'EndTime': datetime(2015, 1, 1),
            'ExpirationTime': datetime(2015, 1, 1),
            'InputDataConfig': {
                'S3Bucket': 'string',
                'S3Key': 'string'
            },
            'OutputDataConfig': {
                'S3Bucket': 'string',
                'S3Key': 'string'
            },
            'LanguageCode': 'en',
            'DataAccessRoleArn': 'string',
            'ManifestFilePath': 'string',
            'KMSKey': 'string',
            'ModelVersion': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • ComprehendMedicalAsyncJobPropertiesList (list) --

      A list containing the properties of each job returned.

      • (dict) --

        Provides information about a detection job.

        • JobId (string) --

          The identifier assigned to the detection job.

        • JobName (string) --

          The name that you assigned to the detection job.

        • JobStatus (string) --

          The current status of the detection job. If the status is FAILED , the Message field shows the reason for the failure.

        • Message (string) --

          A description of the status of a job.

        • SubmitTime (datetime) --

          The time that the detection job was submitted for processing.

        • EndTime (datetime) --

          The time that the detection job completed.

        • ExpirationTime (datetime) --

          The date and time that job metadata is deleted from the server. Output files in your S3 bucket will not be deleted. After the metadata is deleted, the job will no longer appear in the results of the ListEntitiesDetectionV2Job or the ListPHIDetectionJobs operation.

        • InputDataConfig (dict) --

          The input data configuration that you supplied when you created the detection job.

          • S3Bucket (string) --

            The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

            Each file in the document collection must be less than 40 KB. You can store a maximum of 30 GB in the bucket.

          • S3Key (string) --

            The path to the input data files in the S3 bucket.

        • OutputDataConfig (dict) --

          The output data configuration that you supplied when you created the detection job.

          • S3Bucket (string) --

            When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output.

          • S3Key (string) --

            The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

        • LanguageCode (string) --

          The language code of the input documents.

        • DataAccessRoleArn (string) --

          The Amazon Resource Name (ARN) that gives Amazon Comprehend Medical read access to your input data.

        • ManifestFilePath (string) --

          The path to the file that describes the results of a batch job.

        • KMSKey (string) --

          The AWS Key Management Service key, if any, used to encrypt the output files.

        • ModelVersion (string) --

          The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

    • NextToken (string) --

      Identifies the next page of results to return.

list_phi_detection_jobs(**kwargs)

Gets a list of protected health information (PHI) detection jobs that you have submitted.

See also: AWS API Documentation

Request Syntax

response = client.list_phi_detection_jobs(
    Filter={
        'JobName': 'string',
        'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
        'SubmitTimeBefore': datetime(2015, 1, 1),
        'SubmitTimeAfter': datetime(2015, 1, 1)
    },
    NextToken='string',
    MaxResults=123
)
Parameters
  • Filter (dict) --

    Filters the jobs that are returned. You can filter jobs based on their names, status, or the date and time that they were submitted. You can only set one filter at a time.

    • JobName (string) --

      Filters on the name of the job.

    • JobStatus (string) --

      Filters the list of jobs based on job status. Returns only jobs with the specified status.

    • SubmitTimeBefore (datetime) --

      Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted before the specified time. Jobs are returned in ascending order, oldest to newest.

    • SubmitTimeAfter (datetime) --

      Filters the list of jobs based on the time that the job was submitted for processing. Returns only jobs submitted after the specified time. Jobs are returned in descending order, newest to oldest.

  • NextToken (string) -- Identifies the next page of results to return.
  • MaxResults (integer) -- The maximum number of results to return in each page. The default is 100.
Return type

dict

Returns

Response Syntax

{
    'ComprehendMedicalAsyncJobPropertiesList': [
        {
            'JobId': 'string',
            'JobName': 'string',
            'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'PARTIAL_SUCCESS'|'FAILED'|'STOP_REQUESTED'|'STOPPED',
            'Message': 'string',
            'SubmitTime': datetime(2015, 1, 1),
            'EndTime': datetime(2015, 1, 1),
            'ExpirationTime': datetime(2015, 1, 1),
            'InputDataConfig': {
                'S3Bucket': 'string',
                'S3Key': 'string'
            },
            'OutputDataConfig': {
                'S3Bucket': 'string',
                'S3Key': 'string'
            },
            'LanguageCode': 'en',
            'DataAccessRoleArn': 'string',
            'ManifestFilePath': 'string',
            'KMSKey': 'string',
            'ModelVersion': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • ComprehendMedicalAsyncJobPropertiesList (list) --

      A list containing the properties of each job returned.

      • (dict) --

        Provides information about a detection job.

        • JobId (string) --

          The identifier assigned to the detection job.

        • JobName (string) --

          The name that you assigned to the detection job.

        • JobStatus (string) --

          The current status of the detection job. If the status is FAILED , the Message field shows the reason for the failure.

        • Message (string) --

          A description of the status of a job.

        • SubmitTime (datetime) --

          The time that the detection job was submitted for processing.

        • EndTime (datetime) --

          The time that the detection job completed.

        • ExpirationTime (datetime) --

          The date and time that job metadata is deleted from the server. Output files in your S3 bucket will not be deleted. After the metadata is deleted, the job will no longer appear in the results of the ListEntitiesDetectionV2Job or the ListPHIDetectionJobs operation.

        • InputDataConfig (dict) --

          The input data configuration that you supplied when you created the detection job.

          • S3Bucket (string) --

            The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

            Each file in the document collection must be less than 40 KB. You can store a maximum of 30 GB in the bucket.

          • S3Key (string) --

            The path to the input data files in the S3 bucket.

        • OutputDataConfig (dict) --

          The output data configuration that you supplied when you created the detection job.

          • S3Bucket (string) --

            When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output.

          • S3Key (string) --

            The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

        • LanguageCode (string) --

          The language code of the input documents.

        • DataAccessRoleArn (string) --

          The Amazon Resource Name (ARN) that gives Amazon Comprehend Medical read access to your input data.

        • ManifestFilePath (string) --

          The path to the file that describes the results of a batch job.

        • KMSKey (string) --

          The AWS Key Management Service key, if any, used to encrypt the output files.

        • ModelVersion (string) --

          The version of the model used to analyze the documents. The version number looks like X.X.X. You can use this information to track the model used for a particular batch of documents.

    • NextToken (string) --

      Identifies the next page of results to return.

start_entities_detection_v2_job(**kwargs)

Starts an asynchronous medical entity detection job for a collection of documents. Use the DescribeEntitiesDetectionV2Job operation to track the status of a job.

See also: AWS API Documentation

Request Syntax

response = client.start_entities_detection_v2_job(
    InputDataConfig={
        'S3Bucket': 'string',
        'S3Key': 'string'
    },
    OutputDataConfig={
        'S3Bucket': 'string',
        'S3Key': 'string'
    },
    DataAccessRoleArn='string',
    JobName='string',
    ClientRequestToken='string',
    KMSKey='string',
    LanguageCode='en'
)
Parameters
  • InputDataConfig (dict) --

    [REQUIRED]

    Specifies the format and location of the input data for the job.

    • S3Bucket (string) -- [REQUIRED]

      The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

      Each file in the document collection must be less than 40 KB. You can store a maximum of 30 GB in the bucket.

    • S3Key (string) --

      The path to the input data files in the S3 bucket.

  • OutputDataConfig (dict) --

    [REQUIRED]

    Specifies where to send the output files.

    • S3Bucket (string) -- [REQUIRED]

      When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output.

    • S3Key (string) --

      The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

  • DataAccessRoleArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend Medical read access to your input data. For more information, see Role-Based Permissions Required for Asynchronous Operations .

  • JobName (string) -- The identifier of the job.
  • ClientRequestToken (string) --

    A unique identifier for the request. If you don't set the client request token, Amazon Comprehend Medical generates one.

    This field is autopopulated if not provided.

  • KMSKey (string) -- An AWS Key Management Service key to encrypt your output files. If you do not specify a key, the files are written in plain text.
  • LanguageCode (string) --

    [REQUIRED]

    The language of the input documents. All documents must be in the same language.

Return type

dict

Returns

Response Syntax

{
    'JobId': 'string'
}

Response Structure

  • (dict) --

    • JobId (string) --

      The identifier generated for the job. To get the status of a job, use this identifier with the DescribeEntitiesDetectionV2Job operation.

start_phi_detection_job(**kwargs)

Starts an asynchronous job to detect protected health information (PHI). Use the DescribePHIDetectionJob operation to track the status of a job.

See also: AWS API Documentation

Request Syntax

response = client.start_phi_detection_job(
    InputDataConfig={
        'S3Bucket': 'string',
        'S3Key': 'string'
    },
    OutputDataConfig={
        'S3Bucket': 'string',
        'S3Key': 'string'
    },
    DataAccessRoleArn='string',
    JobName='string',
    ClientRequestToken='string',
    KMSKey='string',
    LanguageCode='en'
)
Parameters
  • InputDataConfig (dict) --

    [REQUIRED]

    Specifies the format and location of the input data for the job.

    • S3Bucket (string) -- [REQUIRED]

      The URI of the S3 bucket that contains the input data. The bucket must be in the same region as the API endpoint that you are calling.

      Each file in the document collection must be less than 40 KB. You can store a maximum of 30 GB in the bucket.

    • S3Key (string) --

      The path to the input data files in the S3 bucket.

  • OutputDataConfig (dict) --

    [REQUIRED]

    Specifies where to send the output files.

    • S3Bucket (string) -- [REQUIRED]

      When you use the OutputDataConfig object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output.

    • S3Key (string) --

      The path to the output data files in the S3 bucket. Amazon Comprehend Medical creates an output directory using the job ID so that the output from one job does not overwrite the output of another.

  • DataAccessRoleArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend Medical read access to your input data. For more information, see Role-Based Permissions Required for Asynchronous Operations .

  • JobName (string) -- The identifier of the job.
  • ClientRequestToken (string) --

    A unique identifier for the request. If you don't set the client request token, Amazon Comprehend Medical generates one.

    This field is autopopulated if not provided.

  • KMSKey (string) -- An AWS Key Management Service key to encrypt your output files. If you do not specify a key, the files are written in plain text.
  • LanguageCode (string) --

    [REQUIRED]

    The language of the input documents. All documents must be in the same language.

Return type

dict

Returns

Response Syntax

{
    'JobId': 'string'
}

Response Structure

  • (dict) --

    • JobId (string) --

      The identifier generated for the job. To get the status of a job, use this identifier with the DescribePHIDetectionJob operation.

stop_entities_detection_v2_job(**kwargs)

Stops a medical entities detection job in progress.

See also: AWS API Documentation

Request Syntax

response = client.stop_entities_detection_v2_job(
    JobId='string'
)
Parameters
JobId (string) --

[REQUIRED]

The identifier of the medical entities job to stop.

Return type
dict
Returns
Response Syntax
{
    'JobId': 'string'
}

Response Structure

  • (dict) --
    • JobId (string) --

      The identifier of the medical entities detection job that was stopped.

stop_phi_detection_job(**kwargs)

Stops a protected health information (PHI) detection job in progress.

See also: AWS API Documentation

Request Syntax

response = client.stop_phi_detection_job(
    JobId='string'
)
Parameters
JobId (string) --

[REQUIRED]

The identifier of the PHI detection job to stop.

Return type
dict
Returns
Response Syntax
{
    'JobId': 'string'
}

Response Structure

  • (dict) --
    • JobId (string) --

      The identifier of the PHI detection job that was stopped.

Paginators

The available paginators are: