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 findings in radiology reports Free trial
By:
Latest Version:
5.5.4
This model identifies tests, imaging techniques, and imaging findings entities from radiology reports.
Product Overview
This model is engineered for radiology texts and reports, adeptly identifying entities such as imaging tests, imaging techniques, imaging findings, and more. It also automatically detects the assertion status of the findings: Confirmed, Suspected, Negative, and can find relations between diagnosis, tests, and imaging findings. Developed with radiologists, technicians, and medical researchers in mind, the model brings high accuracy to the extraction of pivotal data points from radiological documentation. Harness the power of this pipeline to enhance diagnostic precision, streamline radiological workflows, and support data-driven clinical decision-making.
Key Data
Version
Type
Model Package
Highlights
The model identifies the following entities in radiology reports:
- ImagingTest,
- Imaging_Technique,
- ImagingFindings,
- OtherFindings,
- BodyPart,
- Direction,
- Test,
- Symptom,
- Disease_Syndrome_Disorder,
- Medical_Device,
- Procedure,
- Measurements,
- Units
The model associated the following assertion statuses to the detected entities:
- Confirmed,
- Suspected,
- Negative.
The model identifies the relations between diagnosis, tests, and imaging findings.
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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.
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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$47.52/hr
running on ml.m4.2xlarge
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$0.48/host/hr
running on ml.m4.2xlarge
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.m4.2xlarge Vendor Recommended | $47.52 |
Usage Information
Model input and output details
Input
Summary
Array of Text Documents { "text": [ "Text document 1", "Text document 2", ... ] } Single Text Document { "text": "Single text document" } JSON Lines (JSONL) {"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 findings in radiology reports
AWS Infrastructure
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