Sold by: Virtusa Corporation - vLifeÂ
Deployed on AWS
Machine Learning model to identify the subjects susceptible to Chronic Kidney Disease within 3 years of onset of Type 2 Diabetes.
Overview
Chronic kidney disease (CKD) is a slow and progressive loss of kidney function over a period leading to permanent kidney failure. Type 2 Diabetes is a pre-cursor for CKD. In this POC, the model identifies the subjects susceptible to CKD within 3 years of onset of Type II diabetes. The model is trained on real world data from state of Indiana in collaboration with Indiana Bio Research Institute. The model is trained on 1000+ features. The identification of a CKD patient is the priority for the model so it weighs False Negatives more intensely than False Positives leaving nothing to chance.
Highlights
- Easy-to-use model quickly determines whether a patients's observations can be used to predict the likeliness of disease.
- Provides the most realistic scenario as it is trained on a large dataset capturing all possible patterns.
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
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.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m4.xlarge instance type, real-time mode | $0.00 |
ml.m4.xlarge Inference (Batch) Recommended | Model inference on the ml.m4.xlarge instance type, batch mode | $0.00 |
ml.m4.4xlarge Inference (Real-Time) | Model inference on the ml.m4.4xlarge instance type, real-time mode | $0.00 |
ml.m5.4xlarge Inference (Real-Time) | Model inference on the ml.m5.4xlarge instance type, real-time mode | $0.00 |
ml.m4.16xlarge Inference (Real-Time) | Model inference on the ml.m4.16xlarge instance type, real-time mode | $0.00 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $0.00 |
ml.p3.16xlarge Inference (Real-Time) | Model inference on the ml.p3.16xlarge instance type, real-time mode | $0.00 |
ml.m4.2xlarge Inference (Real-Time) | Model inference on the ml.m4.2xlarge instance type, real-time mode | $0.00 |
ml.c5.2xlarge Inference (Real-Time) | Model inference on the ml.c5.2xlarge instance type, real-time mode | $0.00 |
ml.p3.2xlarge Inference (Real-Time) | Model inference on the ml.p3.2xlarge instance type, real-time mode | $0.00 |
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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
More info @ virtusa.com/vlife
Additional details
Inputs
- Summary
Chronic Kidney Disease Patient Identifier. See Notebook for additional information.
- Input MIME type
- text/csv
See Input Summary
See Input Summary
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