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.

Extract clinical risk factors Free trial
By:
Latest Version:
5.5.4
Identify key risk factors from medical documents
Product Overview
This model specializes in identifying key risk factors such as Coronary Artery Disease, Diabetes, Family History, Hyperlipidemia, Hypertension, Medications, Obesity, and Smoking Habits in clinical documentation. Designed for precision, it assists healthcare professionals in crucial risk assessment and management.
Key Data
Version
Type
Model Package
Highlights
Process up to 7 M chars per hour for real-time and up to 35 M chars per hour for batch mode.
This model is an efficient solution for the automatic detection and classification of risk factors in patient histories and clinical notes. It utilizes cutting-edge natural language processing techniques to accurately identify risk factors like Diabetes, Hypertension, Obesity, and Smoking, among others. It is tailored to meet the needs of healthcare professionals, clinicians, and medical researchers, providing them with a reliable tool for extracting vital risk factors from various medical documents.
Key Features:
- Efficiently identifies a wide array of risk factors, including Coronary Artery Disease, Diabetes, Family History, and more, ensuring comprehensive patient risk profiling.
- Supports preventive care strategies by providing accurate risk factor detection, aiding in early intervention and management.
- Facilitates evidence-based clinical decision-making by delivering precise information on patient risk factors.
- Enhances patient profiling and healthcare planning by offering high-accuracy data extraction from clinical narratives.
This model is invaluable in the healthcare sector, offering a robust tool for clinicians and researchers to optimize patient care and preventive strategies. It ensures precise risk factor identification, contributing to better patient outcomes and informed clinical decision-making. Covered entities: CAD, DIABETES, FAMILY_HIST, HYPERLIPIDEMIA, HYPERTENSION, MEDICATION, OBESE, PHI, SMOKER.
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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$23.76/hr
running on ml.m4.xlarge
Model Batch Transform$47.52/hr
running on ml.m4.2xlarge
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$0.48/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 To use the model for text prediction, you need to provide input in one of the following supported formats:
Single Text Document { "text": "Single text document" }
Array of Text Documents
{ "text": [ "Text document 1", "Text document 2", ] }
- JSON Lines (JSONL) Format {"text": "Text document 1"} {"text": "Text document 2"}
Input MIME type
application/json, application/jsonlinesSample input 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
Extract clinical risk factors
For any assistance, please reach out to support@johnsnowlabs.com.
AWS Infrastructure
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