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.
Patient Eligibility for Cancer Trials
Latest Version:
1
Deep Learning model to predict the eligibility of a patient for a cancer clinical trial after going through patient's diagnosis notes.
Product Overview
Interventional cancer clinical trials are generally too restrictive, and some patients are often excluded on the basis of comorbidity, past or concomitant treatments, or the fact that they are over a certain age. The efficacy and safety of new treatments for patients with these characteristics are, therefore, not defined. In this work, we built a model to automatically predict whether short clinical statements were considered inclusion or exclusion criteria.
Key Data
Version
Categories
Type
Model Package
Highlights
Easy-to-use model quickly determines the eligibility of a patient for a cancer clinical trial.
Provides the most realistic scenario as it is trained on a large dataset capturing all possible patterns.
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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.
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$0.00/hr
running on ml.m4.xlarge
Model Batch Transform$0.00/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
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.m4.4xlarge | $0.00 | |
ml.m5.4xlarge | $0.00 | |
ml.m4.16xlarge | $0.00 | |
ml.m5.2xlarge | $0.00 | |
ml.p3.16xlarge | $0.00 | |
ml.m4.2xlarge | $0.00 | |
ml.c5.2xlarge | $0.00 | |
ml.p3.2xlarge | $0.00 | |
ml.c4.2xlarge | $0.00 | |
ml.m4.10xlarge | $0.00 | |
ml.c4.xlarge | $0.00 | |
ml.m5.24xlarge | $0.00 | |
ml.c5.xlarge | $0.00 | |
ml.p2.xlarge | $0.00 | |
ml.m5.12xlarge | $0.00 | |
ml.p2.16xlarge | $0.00 | |
ml.c4.4xlarge | $0.00 | |
ml.m5.xlarge | $0.00 | |
ml.c5.9xlarge | $0.00 | |
ml.m4.xlarge Vendor Recommended | $0.00 | |
ml.c5.4xlarge | $0.00 | |
ml.p3.8xlarge | $0.00 | |
ml.m5.large | $0.00 | |
ml.c4.8xlarge | $0.00 | |
ml.p2.8xlarge | $0.00 | |
ml.c5.18xlarge | $0.00 |
Usage Information
Fulfillment Methods
Amazon SageMaker
Patient Eligibility for Cancer Trials - Identifier. See Notebook for additional information.
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Support Information
AWS Infrastructure
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