Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique
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Updated
Feb 25, 2018 - Python
Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique
Improving Information Extraction from Pathology Reports using Named Entity Recognition
The first GANs-based omics-to-omics translation framework
A Platypus-based variant calling pipeline for cancer data
A Python client for the cbioPortal Cancer API.
An example of predicting breast cancer using existing data to learn with decision trees (scikit-learn/python)
Feature selection comparison in breath cancer dataset
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Using data from the CDC to track diseases and what might be their causes. Heavily based on data analysis. STILL UNDER CONSTRUCTION!
Recursive Multi-view Integration for Subtypes Identification
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Final-year project: System for aggregation and structured querying of cancer pathway data
Diagnostic Cancer Solution - Machine Learning APP with Wisconsin Breast Cancer Database.
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