Sold by: John Snow LabsÂ
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.
IMPORTANT USAGE INFORMATION:
After subscribing to this product and creating a SageMaker endpoint, billing occurs on an HOURLY BASIS for as long as the endpoint is running.
-Charges apply even if the endpoint is idle and not actively processing requests.
-To stop charges, you MUST DELETE the endpoint in your SageMaker console.
-Simply stopping requests will NOT stop billing.
This ensures you are only billed for the time you actively use the service.
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 automatically detects and classifies risk factors in patient histories and clinical notes using advanced NLP. It accurately identifies conditions such as diabetes, hypertension, obesity, and smoking, providing healthcare professionals and researchers with a reliable tool for extracting critical information from medical documents.
- **Key Features:* - Identifies a wide array of risk factors, like Coronary Artery Disease, Diabetes, Family History, etc , ensuring comprehensive patient risk profiling. - Preventive care strategies by providing accurate risk factor detection, aiding in early intervention and management. - Evidence-based clinical decision-making by delivering precise information on patient risk factors. - 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.
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Free trial
Try this product free for 15 days according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m4.2xlarge Inference (Batch) Recommended | Model inference on the ml.m4.2xlarge instance type, batch mode | $47.52 |
ml.m4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m4.xlarge instance type, real-time mode | $23.76 |
ml.m4.xlarge Inference (Batch) | Model inference on the ml.m4.xlarge instance type, batch mode | $23.76 |
Vendor refund policy
No refunds are possible.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Model optimization
Additional details
Inputs
- 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/jsonlines
https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/en.med_ner.risk_factors.pipeline/inputs/real-time
https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/en.med_ner.risk_factors.pipeline/inputs/batch
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
text | Contains the text to analyze. | Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out to support@johnsnowlabs.com .
AWS infrastructure support
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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