Cancer-Detection-Model

Project Abstract & Details

A machine learning–based cancer detection model designed to analyze medical data (such as imaging, histopathology, or clinical features) to identify patterns indicative of malignant disease. The model leverages supervised learning to distinguish between cancerous and non-cancerous cases, enabling early detection, risk stratification, and decision support for clinicians. It aims to improve diagnostic accuracy, reduce human error, and support timely intervention while complementing, not replacing, clinical judgment.