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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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Detect Drug Side Effect Narratives Free trial

Latest Version:
5.2.8
Classify health-related text in colloquial language according to the presence or absence of mentions of drug side effects.

    Product Overview

    This model is specialized in the classification of health-related textual data, particularly focusing on colloquial expressions. Its core functionality is to accurately identify whether the text includes references to side effects stemming from drug usage. This capability is crucial for monitoring and analyzing patient feedback, social media discussions, and informal patient-reported outcomes that are often expressed in non-technical language. Leveraging state-of-the-art machine learning algorithms, the model is adept at parsing the nuances of everyday language used by individuals when describing their experiences with medications. It has undergone extensive training and fine-tuning on a diverse dataset comprising medical forums, patient testimonials, and other sources of informal health-related discourse. This ensures the model's effectiveness in recognizing a wide array of vernacular expressions and idioms pertaining to side effects.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • This model can be used across various domains within the healthcare sector, including but not limited to pharmacovigilance, drug safety monitoring, and patient care improvement initiatives. It enables stakeholders to harness the power of unstructured text data, transforming it into actionable insights regarding drug safety and efficacy. By automating the detection of side effect mentions, healthcare professionals and organizations can proactively address patient concerns, enhance drug safety protocols, and contribute to the overall improvement of healthcare delivery.

    • This model is particularly valuable for organizations looking to integrate advanced NLP capabilities into their healthcare analytics tools, patient feedback systems, and drug safety monitoring frameworks.

    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$9.84/hr

    running on ml.m4.xlarge

    Model Batch Transform$9.84/hr

    running on ml.m4.xlarge

    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$0.24/host/hr

    running on ml.m4.xlarge

    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
    $9.84

    Usage Information

    Model input and output details

    Input

    Summary

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

    1. Single Text Document Provide a single text document as a string.

    { "text": "Single text document" }

    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",
      ] }
    Input MIME type
    application/json
    Sample input data

    Output

    Summary

    The output consists of a JSON object with the following structure: { "predictions": [ { "prediction": "label", "confidence": Score }, ... ] }

    Output MIME type
    application/json
    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

    Detect Drug Side Effect Narratives

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

    AWS Infrastructure

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    Refund Policy

    No refunds are possible.

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