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.

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

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.

Cancer Predisposition Sequencing Reporter (CPSR)

Cancer Whitepaper

cfDNAPro specializes in standardized and robust cfDNA fragmentomic analysis

Automated KFSYSCC IRB document preparation — 43 forms, 11 categories, one command. Because your time is better spent on science, not paperwork.

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.

Gently mending for breast cancer patients.

Crossmapped phenotype ontologies for the oncology domain

A unified downloader+preprocessor for cancer genomics datasets

📎 About MIMBCD-UI Project

Some accessible radiomics datas were provided in this link.

Anticancer Peptide Identification employing Multi-headed Deep-CNN