Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing

Personalized Genomics and Proteomics. Main diet: Ensembl, side dishes: SNPs

A community-maintained repository of cancer clinical knowledge bases and databases focused on cancer variants.

Personal Cancer Genome Reporter (PCGR)

Fast and accurate gene fusion detection from RNA-Seq data

This project is all about a Machine Learning based Medical Test web app which makes predictions about various diseases using the concept of machine learning.

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

A list of web-based interactive biological data visualizations.

Health Check ✔ is a Machine Learning Web Application made using Flask that can predict mainly three diseases i.e. Diabetes, Heart Disease, and Cancer.

Training and evaluating a variational autoencoder for pan-cancer gene expression data

P-NET, Biologically informed deep neural network for prostate cancer classification and discovery

Detect and visualize target mutations by scanning FastQ files directly

Detect germline or somatic variants from normal or tumour/normal whole-genome or targeted sequencing

Building classifiers using cancer transcriptomes across 33 different cancer-types

Gene fusion detection and visualization

A Slicer extension to provide a GUI around pyradiomics

Opensource radiation treatment planning system in Python [AAPM'23]

A collection of small-sample, high-dimensional microarray data sets to assess machine-learning algorithms and models.