colorectal-cancer
There are 20 repositories under colorectal-cancer topic.
DebeshJha/GastroVision
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection https://drive.google.com/drive/folders/1T35gqO7jIKNxC-gVA2YVOMdsL7PSqeAa?usp=sharing
DebeshJha/PolypGen
A multi-centre polyp detection and segmentation dataset for generalisability assessment https://www.nature.com/articles/s41597-023-01981-y
bupt-ai-cz/Label-Noise-Robust-Training
Noise Robust Learning with Hard Example Aware for Pathological Image classification
soumitri2001/DMTNet-CRCH
Official Implementation of our paper "Supervision meets Self-Supervision: A Deep Multitask Network for Colorectal Cancer Histopathological Analysis" [Best Paper Award at MISP 2022]
anjunatarajan/Colorectal-Cancer-Survival-Analysis-MSK
This repository contains all machine learning and statistical models used to analyze the landscape of colorectal cancer.
ionut-d/TCGA-data-mining-Wnt-CRC
UNSUPERVISED MACHINE LEARNING (CLUSTERING): TCGA data mining for studying the system of interactions between sub-branches of Wnt signalling pathway in colorectal cancer
lely475/CTPLab_SemiCOL2023
DL-model for multi-class tissue segmentation in colorectal cancer H&E slides, developed as part of the SemiCOL2023 Challenge.
phoebe2199/crc-diagnosis-app
Diagnosing colorectal cancer from histopathology images using deep learning: final project code.
BehshadR/Colorectal-Cancer-Histology-Transfer-Learning-and-Fine-Tuning
Transfer learning & fine-tuning in Tensorflow for classification of textures in colorectal cancer histology
DanielCorralesAlonso/CRC_Risk_BN
Colorectal cancer risk mapping through Bayesian Networks
ala-sk98/CDC
Colorectal Disease Classification Using ResNet and ResNeXt
DanielCorralesAlonso/Decision_Model_Screening_CRC
Decision model for colorrectal cancer screening. Based on bayesian networks and influence diagrams
graysoncroom/Colorectal-Cancer-Detector
Determines if a given Colorectal tissue image is cancerous or healthy using methods from Topology for the input embedding (TDA).
HuzeyfeAyaz/CRC_Prediction_with_Immune_SNP_Profiles
The goal of this analysis is to explore the machine learning-based automatic diagnosis of colorectal patients based on the single nucleotide polymorphisms (SNP). Such a computational approach may be used complementary to other diagnosis tools, such as, biopsy, CT scan, and MRI. Moreover, it may be used as a low-cost screening for colorectal cancers
nedaghohabi/CRC-Microbiome-Classification
Prediction of colorectal cancer (CRC) phenotype based on Microbiome Metagenomics
SamuelBernard4/Epigenetic-Modeling-for-Cancer-Detection
Combining epigenetic modeling with machine learning for colorectal cancer detection
soumitri2001/SnapEnsemFS
Based on our paper "SnapEnsemFS: A Snapshot Ensembling-based Deep Feature Selection Model for Colorectal Cancer Histological Analysis" published in Scientific Reports, Nature (2023).