
Overview
Non-Hodgkin lymphoma (also known as non-Hodgkin’s lymphoma, NHL, or sometimes just lymphoma) is a cancer that starts in white blood cells called lymphocytes, which are part of the body’s immune system. This model illustrates the potential of Deep Learning - in contributing to the automation of cancer diagnosis, by proposing a method to classify the subtypes of Lymphoma. This model is not intended for medical and diagnostic purpose.
Highlights
- Multi-class classifier model that classifies Lymphoma Images as Chronic Lymphocytic Leukaemia, Follicular and Mantle Cell Lymphoma
- Trained using AlexNet (CNN Architecture)
- Acknowledgement: Janowczyk A, Madabhushi A. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases. J Pathol Inform 2016;7:29. (http://www.andrewjanowczyk.com/use-case-7-lymphoma-sub-type-classification/)
Details
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Features and programs
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Pricing
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m4.xlarge Inference (Batch) Recommended | Model inference on the ml.m4.xlarge instance type, batch mode | $0.00 |
ml.m4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m4.xlarge instance type, real-time mode | $0.00 |
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Since you are not being charged currently for the use of this software there will be no refund of any charges.
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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.
Version release notes
First version released to AWS ML Marketplace
Additional details
Inputs
- Summary
Download the Jupyter notebook in "Additional Resources" section and follow readme.txt provided.
- Input MIME type
- image/tiff
Resources
Vendor resources
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