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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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Clinical Text Analysis Free trial

By:
John Snow Labs
Latest Version:
5.5.4
Transform clinical text into structured data with NLP, extracting entities, assigning statuses, and linking relationships
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    Product Overview

    Clinical entity detection, assertion status assignment, and relation extraction are essential in medical text analysis. These techniques enable healthcare professionals, researchers, and medical NLP practitioners to derive valuable insights from clinical literature, electronic health records, and patient notes, enhancing the understanding and management of patient data. This API uses state of the art medical models and is perfect for healthcare data analysts, clinical researchers, and healthcare AI application developers looking to extract detailed and actionable insights from unstructured clinical text.

    Key Data

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

    Highlights

    • Key Features:

      • Entity Recognition: Extracts a wide array of clinical entities using state of the art medical model.

      • Assertion Status : Determines the assertion status of each entity and classifies it as hypothetical, past, planned, present, and more.

      • Relation Extraction: Links related entities, like drugs with their dosages and frequencies, test results with the tests, and more, which is crucial for building a connected data graph from disjointed text.

    • Supported Labels:

      • Clinical Entity Labels: Includes categories like Age, Gender, Symptoms, Diseases, Medications, Vital Signs, and many others.
      • Assertion Status Labels: Categorizes entities into statuses such as Hypothetical, Past, Present, Planned, and others to provide context.
      • Relation Extraction Labels: Identifies relations such as is_finding_of, is_date_of, is_result_of, Drug_BrandName-Dosage, Drug_BrandName-Frequency, Drug_BrandName-Route , Drug_BrandName-Strength, Drug_Ingredient-Dosage, Drug_Ingredient-Frequency, Drug_Ingredient-Route, Drug_Ingredient-Strength.

    • Process up to 4 M chars per hour for real-time and up to 17 M chars per hour for batch mode.

      Benchmarking information :

    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$23.76/hr

    running on ml.m4.xlarge

    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$0.24/host/hr

    running on ml.m4.xlarge

    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.xlarge
    Vendor Recommended
    $23.76

    Usage Information

    Model input and output details

    Input

    Summary

    To use the model, you need to provide input in one of the following supported formats:

    1. Array of Text Documents Use an array containing multiple text documents. Each element represents a separate text document. { "text": [
       "Text document 1",
 "Text document 2",
      ] }
    2. Single Text Document Provide a single text document as a string { "text": "Single text document" }
    3. 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
    Conatins the text to be analyzed.
    Required
    Yes
    Data type
    FreeText

    Output

    Summary

    The full description of the output Output Format .

    Output MIME type
    application/json, application/jsonlines
    Sample output data
    Expand all output descriptions
    Field name
    document
    Description
    The original input for which predictions are made
    Always returned
    Yes
    Data type
    FreeText
    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
    Admission_Discharge,Age,Alcohol,Allergen,BMI,Birth_Entity,Blood_Pressure,Cerebrovascular_Disease,Clinical_Dept, Communicable_Disease,Date,Death_Entity,Diabetes,Diet,Direction,Disease_Syndrome_Disorder, Dosage,Drug_BrandName,Drug_Ingredient,Duration,EKG_Findings,Employment, External_body_part_or_region,Family_History_Header,Fetus_NewBorn,Form,Frequency, Gender,HDL,Heart_Disease,Height,Hyperlipidemia,Hypertension,ImagingFindings,Imaging_Technique, Injury_or_Poisoning,Internal_organ_or_component,Kidney_Disease,LDL,Labour_Delivery,Medical_Device, Medical_History_Header,Modifier,O2_Saturation,Obesity,Oncological,Overweight,Oxygen_Therapy, Pregnancy,Procedure,Psychological_Condition,Pulse,Race_Ethnicity,Relationship_Status,RelativeDate,RelativeTime, Respiration,Route,Section_Header,Sexually_Active_or_Sexual_Orientation,Smoking,Social_History_Header, Strength,Substance,Substance_Quantity,Symptom,Temperature,Test,Test_Result,Time,Total_Cholesterol, Treatment,Triglycerides,VS_Finding,Vaccine,Vaccine_Name,Vital_Signs_Header,Weight
    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
    document
    Description
    The original input text for which assertions are made.
    Always returned
    Yes
    Data type
    FreeText
    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
    Admission_Discharge,Age,Alcohol,Allergen,BMI,Birth_Entity,Blood_Pressure,Cerebrovascular_Disease,Clinical_Dept, Communicable_Disease,Date,Death_Entity,Diabetes,Diet,Direction,Disease_Syndrome_Disorder, Dosage,Drug_BrandName,Drug_Ingredient,Duration,EKG_Findings,Employment, External_body_part_or_region,Family_History_Header,Fetus_NewBorn,Form,Frequency, Gender,HDL,Heart_Disease,Height,Hyperlipidemia,Hypertension,ImagingFindings,Imaging_Technique, Injury_or_Poisoning,Internal_organ_or_component,Kidney_Disease,LDL,Labour_Delivery,Medical_Device, Medical_History_Header,Modifier,O2_Saturation,Obesity,Oncological,Overweight,Oxygen_Therapy, Pregnancy,Procedure,Psychological_Condition,Pulse,Race_Ethnicity,Relationship_Status,RelativeDate,RelativeTime, Respiration,Route,Section_Header,Sexually_Active_or_Sexual_Orientation,Smoking,Social_History_Header, Strength,Substance,Substance_Quantity,Symptom,Temperature,Test,Test_Result,Time,Total_Cholesterol, Treatment,Triglycerides,VS_Finding,Vaccine,Vaccine_Name,Vital_Signs_Header,Weight
    Field name
    assertion
    Description
    Assertion status.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    Hypothetical, Someoneelse, Past, Absent, Family, Planned, Possible, Present
    Field name
    assertion_confidence
    Description
    Confidence score associated with the assertion.
    Always returned
    Yes
    Data type
    Continuous (Float)
    Range
    Min: 0
    Max: 1
    Field name
    document
    Description
    The original input text for which relations are identified.
    Always returned
    Yes
    Data type
    FreeText
    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
    Admission_Discharge,Age,Alcohol,Allergen,BMI,Birth_Entity,Blood_Pressure,Cerebrovascular_Disease,Clinical_Dept, Communicable_Disease,Date,Death_Entity,Diabetes,Diet,Direction,Disease_Syndrome_Disorder, Dosage,Drug_BrandName,Drug_Ingredient,Duration,EKG_Findings,Employment, External_body_part_or_region,Family_History_Header,Fetus_NewBorn,Form,Frequency, Gender,HDL,Heart_Disease,Height,Hyperlipidemia,Hypertension,ImagingFindings,Imaging_Technique, Injury_or_Poisoning,Internal_organ_or_component,Kidney_Disease,LDL,Labour_Delivery,Medical_Device, Medical_History_Header,Modifier,O2_Saturation,Obesity,Oncological,Overweight,Oxygen_Therapy, Pregnancy,Procedure,Psychological_Condition,Pulse,Race_Ethnicity,Relationship_Status,RelativeDate,RelativeTime, Respiration,Route,Section_Header,Sexually_Active_or_Sexual_Orientation,Smoking,Social_History_Header, Strength,Substance,Substance_Quantity,Symptom,Temperature,Test,Test_Result,Time,Total_Cholesterol, Treatment,Triglycerides,VS_Finding,Vaccine,Vaccine_Name,Vital_Signs_Header,Weight
    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
    Admission_Discharge,Age,Alcohol,Allergen,BMI,Birth_Entity,Blood_Pressure,Cerebrovascular_Disease,Clinical_Dept, Communicable_Disease,Date,Death_Entity,Diabetes,Diet,Direction,Disease_Syndrome_Disorder, Dosage,Drug_BrandName,Drug_Ingredient,Duration,EKG_Findings,Employment, External_body_part_or_region,Family_History_Header,Fetus_NewBorn,Form,Frequency, Gender,HDL,Heart_Disease,Height,Hyperlipidemia,Hypertension,ImagingFindings,Imaging_Technique, Injury_or_Poisoning,Internal_organ_or_component,Kidney_Disease,LDL,Labour_Delivery,Medical_Device, Medical_History_Header,Modifier,O2_Saturation,Obesity,Oncological,Overweight,Oxygen_Therapy, Pregnancy,Procedure,Psychological_Condition,Pulse,Race_Ethnicity,Relationship_Status,RelativeDate,RelativeTime, Respiration,Route,Section_Header,Sexually_Active_or_Sexual_Orientation,Smoking,Social_History_Header, Strength,Substance,Substance_Quantity,Symptom,Temperature,Test,Test_Result,Time,Total_Cholesterol, Treatment,Triglycerides,VS_Finding,Vaccine,Vaccine_Name,Vital_Signs_Header,Weight
    Field name
    relation
    Description
    Type of relation identified.
    Always returned
    Yes
    Data type
    Categorical
    Allowed values
    is_finding_of, is_date_of, is_result_of, Drug_BrandName-Dosage, Drug_BrandName-Frequency, Drug_BrandName-Route , Drug_BrandName-Strength, Drug_Ingredient-Dosage, Drug_Ingredient-Frequency, Drug_Ingredient-Route, Drug_Ingredient-Strength, 0
    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

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    Support Information

    Clinical Text Analysis

    For any assistance, please reach out to support@johnsnowlabs.com.

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