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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 adverse drug events (ADE) Free trial

Latest Version:
5.5.4
Detects adverse reactions of drugs (ADE) from reviews, tweets, and medical text.

    Product Overview

    This model is engineered for the extraction of adverse drug events (ADEs) from unstructured clinical texts, leveraging several components finely tuned for this purpose: - Entity Recognition: Initially, the model accurately identifies entities related to adverse events (such as rash, nausea) and drug. - Assertion Status Detection: Subsequently, it assigns an assertion status (e.g., present, negated, historical, hypothetical) to each identified ADE entity, taking into account the surrounding context. - Document Classification: The model then classifies the entire document, discerning whether it contains a report of an ADE. This classification aids in filtering documents more likely to possess relevant ADE information. Covered classes: ADE, noADE - Relation Extraction: detection of relationships between the extracted ADE entities and drug entities. Covered relations: 0 (absent), 1 (present).

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Analyze up to 1.4 M chars per hour for real time processing and up to 3.5 M chars per hour for batch processing.

      The model addresses the critical need to identify adverse drug reactions (ADRs) - unintended and sometimes harmful responses to medications. It's crucial for healthcare professionals and patients to understand the potential side effects for informed care and decision-making. Especially in cases with multiple drug mentions, this model proficiently correlates drugs with their respective adverse reactions, discerning if an event is drug-induced.

    • In the digital era, patients frequently share medication experiences across various platforms like online reviews, social media, and forums. This model meticulously scans such diverse content, including clinical notes, to detect drug-associated adverse reactions. It serves as a proactive tool for early ADR identification, thereby enhancing patient safety and refining drug prescription practices.

    • Covered entities: DRUG, ADE. Covered assertion statuses: absent, present, conditional, associated_with_someone_else, hypothetical, possible. Relations: 0 (absent), 1 (present). Covered classes: ADE, noADE

    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

    Input Format

    1. Single Text Document { "text": "Single text document" }
    2. Array of Text Documents { "text": [
       "Text document 1",
       "Text document 2",
       ...
      ] }
    3. JSON Lines (JSONL) Format {"text": "Text document 1"} {"text": "Text document 2"}
    Input MIME type
    application/json, application/jsonlines
    Sample input data

    Output

    Summary

    The output is a json structure containing all named entites predicted , all assertions for each named entity predicted, all predicted relations between indentified named entities and all sentence level predicted classifications for all extracted sentences - for each input document.

    See the details of the output structure here

    Output MIME type
    application/json, application/jsonlines
    Sample output data

    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 adverse drug events (ADE)

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

    AWS Infrastructure

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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    Refund Policy

    No refunds are possible.

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