Multi-cancer classification using CNN
Saksham Madaan, Nishant K. Meena, Mihir Goswami, Manoj Kumar · 2025
The goal of this project is to create a deep learning model for multi-cancer classification using PyTorch that is both scalable and reliable. The integration of several data sources, including histological pictures and clinical data, is emphasized to provide a thorough and precise tumor classification. The framework aims to offer a strong basis for future research attempts in cancer categorization by utilizing PyTorch&s;s capabilities. The main objective is to meet the urgent demand for reliable methods that can accurately differentiate between various tumor kinds. The model prioritizes scalability to ensure its application in a variety of research contexts and to handle the increasing volume and complexity of cancer data. This project acknowledges PyTorch&s;s critical contribution in enabling the creation of sophisticated deep learning models and promoting innovation in the field of cancer classification. This project seeks to promote cancer research and clinical practice by providing a robust and flexible framework that will open doors to the investigation of increasingly complex algorithms and techniques.