This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

A deep learning approach to predicting breast tumor proliferation scores for the TUPAC16 challenge

PhysiCell: Scientist end users should use latest release! Developers please fork the development branch and submit PRs to the dev branch. Thanks!

AI-based pathology predicts origins for cancers of unknown primary - Nature

🌲 An easy-to-use and scalable toolkit for genomic alteration signature (a.k.a. mutational signature) analysis and visualization in R https://shixiangwang.github.io/sigminer/reference/index.html

Chaste - Cancer Heart And Soft Tissue Environment - main public repository.

Tool to visualize gigantic pathology images and use AI to segment cancer cells and present as an overlay

An R package for studying mutational signatures and structural variant signatures along clonal evolution in cancer.

DeepSpot: Deep learning model for predicting spatial transcriptomics from H&E histopathology images. Supports spot-level (Visium) and single-cell (Xenium) resolution.

Cancer Predisposition Sequencing Reporter (CPSR)

Cancer Whitepaper

cfDNAPro specializes in standardized and robust cfDNA fragmentomic analysis

This pipeline provides a way to perform pharmaceutical compounds virtual screening using similarity-based analysis, ligand-based and structure-based techniques. The pipeline contains a collections of modules to perform a variety of analysis.

A unified downloader+preprocessor for cancer genomics datasets

📎 About MIMBCD-UI Project

Some accessible radiomics datas were provided in this link.

Crossmapped phenotype ontologies for the oncology domain

Anticancer Peptide Identification employing Multi-headed Deep-CNN

📎 About MIDA Project

Image classification on lung and colon cancer histopathological images through Capsule Networks or CapsNets.