GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection (https://osf.io/84e7f/)
Noise Robust Learning with Hard Example Aware for Pathological Image classification
Official Implementation of our paper "Supervision meets Self-Supervision: A Deep Multitask Network for Colorectal Cancer Histopathological Analysis" [Best Paper Award at MISP 2022]
DL-model for multi-class tissue segmentation in colorectal cancer H&E slides, developed as part of the SemiCOL2023 Challenge.
Colorectal cancer risk mapping through Bayesian Networks
Based on our paper "SnapEnsemFS: A Snapshot Ensembling-based Deep Feature Selection Model for Colorectal Cancer Histological Analysis" published in Scientific Reports, Nature (2023).
Combining epigenetic modeling with machine learning for colorectal cancer detection
Decision model for colorrectal cancer screening. Based on bayesian networks and influence diagrams
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