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Amazon Sagemaker

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

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Extract findings in radiology reports Free trial

By:
John Snow Labs
Latest Version:
5.5.4
This model identifies tests, imaging techniques, and imaging findings entities from radiology reports.
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    Product Overview

    This model is engineered for radiology texts and reports, adeptly identifying entities such as imaging tests, imaging techniques, imaging findings, and more. It also automatically detects the assertion status of the findings: Confirmed, Suspected, Negative, and can find relations between diagnosis, tests, and imaging findings. Developed with radiologists, technicians, and medical researchers in mind, the model brings high accuracy to the extraction of pivotal data points from radiological documentation. Harness the power of this pipeline to enhance diagnostic precision, streamline radiological workflows, and support data-driven clinical decision-making.

    Key Data

    Version
    5.5.4
    Usage Instructions
    Release Notes
    By
    John Snow Labs
    Categories
    Natural Language Processing
    Names Entity Recognition - NER
    Healthcare & Life Sciences
    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • The model identifies the following entities in radiology reports:

      • ImagingTest,
      • Imaging_Technique,
      • ImagingFindings,
      • OtherFindings,
      • BodyPart,
      • Direction,
      • Test,
      • Symptom,
      • Disease_Syndrome_Disorder,
      • Medical_Device,
      • Procedure,
      • Measurements,
      • Units

    • The model associated the following assertion statuses to the detected entities:

      • Confirmed,
      • Suspected,
      • Negative.

    • The model identifies the relations between diagnosis, tests, and imaging findings.

    Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us

    Pricing Information

    Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.

    Contact us to request contract pricing for this product.


    Estimating your costs

    Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.

    Version
    Region

    Software Pricing

    Model Realtime Inference$47.52/hr

    running on ml.m4.2xlarge

    Model Batch Transform$47.52/hr

    running on ml.m4.2xlarge

    Infrastructure Pricing

    With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
    Learn more about SageMaker pricing

    SageMaker Realtime Inference$0.48/host/hr

    running on ml.m4.2xlarge

    SageMaker Batch Transform$0.48/host/hr

    running on ml.m4.2xlarge

    About Free trial

    Try this product for 15 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.

    Model Realtime Inference

    For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.
    InstanceType
    Realtime Inference/hr
    ml.m4.2xlarge
    Vendor Recommended
    $47.52

    Usage Information

    Model input and output details

    Input

    Summary

    Array of Text Documents { "text": [ "Text document 1", "Text document 2", ... ] } Single Text Document { "text": "Single text document" } JSON Lines (JSONL) {"text": "Text document 1"} {"text": "Text document 2"}

    Input MIME type
    application/json, application/jsonlines
    Sample input data
    Expand all input descriptions
    Field name
    text
    Description
    Contains the text to analyze.
    Required
    Yes
    Data type
    FreeText

    Output

    Summary

    See the full output documentation here

    Output MIME type
    application/json, application/jsonlines
    Sample output data
    Expand all output descriptions
    Field name
    ner_chunk
    Description
    Named entity recognized in the document.
    Always returned
    Yes
    Data type
    FreeText
    Field name
    begin
    Description
    Starting character index of the named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    end
    Description
    Ending character index of the named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    ner_label
    Description
    Label assigned to the named entity.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    Imaging_Test, Imaging_Technique, ImagingFindings, OtherFindings ,BodyPart ,Direction ,Test ,Symptom ,Disease_Syndrome_Disorder ,Medical_Device ,Procedure ,Measurements ,Units ,Gender ,Metastasis ,Invasion ,Route ,Treatment ,Drug ,Form ,Frequency ,Dosage ,Date ,Test_Result ,Medical_Device
    Field name
    ner_confidence:
    Description
    Confidence score associated with the ner prediction.
    Always returned
    Yes
    Data type
    Continuous (Float)
    Range
    Min: 0
    Max: 1
    Field name
    ner_chunk
    Description
    Named entity associated with the assertion.
    Always returned
    Yes
    Data type
    FreeText
    Field name
    begin
    Description
    Starting character index of the named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    end
    Description
    Ending character index of the named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    ner_label
    Description
    Label assigned to the named entity.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    Imaging_Test, Imaging_Technique, ImagingFindings, OtherFindings ,BodyPart ,Direction ,Test ,Symptom ,Disease_Syndrome_Disorder ,Medical_Device ,Procedure ,Measurements ,Units ,Gender ,Metastasis ,Invasion ,Route ,Treatment ,Drug ,Form ,Frequency ,Dosage ,Date ,Test_Result ,Medical_Device
    Field name
    assertion
    Description
    Assertion status
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    Confirmed, Suspected, Negative
    Field name
    ner_chunk1
    Description
    First named entity involved in the relation
    Always returned
    Yes
    Data type
    FreeText
    Field name
    ner_chunk1_begin
    Description
    Starting character index of the first named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    ner_chunk1_end
    Description
    Ending character index of the first named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    ner_label1
    Description
    Label assigned to the first named entity.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    Imaging_Test, Imaging_Technique, ImagingFindings, OtherFindings ,BodyPart ,Direction ,Test ,Symptom ,Disease_Syndrome_Disorder ,Medical_Device ,Procedure ,Measurements ,Units ,Gender ,Metastasis ,Invasion ,Route ,Treatment ,Drug ,Form ,Frequency ,Dosage ,Date ,Test_Result ,Medical_Device
    Field name
    ner_chunk2
    Description
    Second named entity involved in the relation.
    Always returned
    Yes
    Data type
    FreeText
    Field name
    ner_chunk2_begin
    Description
    Starting character index of the second named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    ner_chunk2_end
    Description
    Ending character index of the second named entity chunk within the document.
    Always returned
    Yes
    Data type
    Integer
    Range
    Field name
    ner_label2
    Description
    Label assigned to the second named entity.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    Imaging_Test, Imaging_Technique, ImagingFindings, OtherFindings ,BodyPart ,Direction ,Test ,Symptom ,Disease_Syndrome_Disorder ,Medical_Device ,Procedure ,Measurements ,Units ,Gender ,Metastasis ,Invasion ,Route ,Treatment ,Drug ,Form ,Frequency ,Dosage ,Date ,Test_Result ,Medical_Device
    Field name
    relations
    Description
    Type of relation identified.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    is_related,not_related
    Field name
    relation_confidence
    Description
    Confidence score associated with the relation.
    Always returned
    Yes
    Data type
    Continuous (Float)
    Range
    Min: 0
    Max: 1

    Sample notebook

    Additional Resources

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)

    Support Information

    Extract findings in radiology reports

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