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.
Detect Drug Side Effect Narratives Free trial
By:
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
Version
Type
Model Package
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.
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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 PricingWith 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
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:
- Single Text Document Provide a single text document as a string.
{ "text": "Single text document" }
- 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/jsonSample input data
Output
Summary
The output consists of a JSON object with the following structure: { "predictions": [ { "prediction": "label", "confidence": Score }, ... ] }
Output MIME type
application/jsonSample output data
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
Detect Drug Side Effect Narratives
For any assistance, please reach out to support@johnsnowlabs.com.
AWS Infrastructure
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