MATLAB Code Implementation for Breast Cancer Classification

The breast cancer classification program is a diagnostic tool designed to determine whether a patient has breast cancer. It analyzes various patient factors including breast tissue characteristics, age, gender, and family medical history through machine learning algorithms to generate accurate classifications. The implementation typically involves preprocessing medical data, feature extraction using techniques like wavelet transforms, and training classification models such as Support Vector Machines (SVM) or neural networks. This program includes partial original datasets that facilitate model validation and help physicians make more precise diagnoses, thereby improving treatment success rates. The code structure may include key functions for data normalization, cross-validation, and performance evaluation using metrics like accuracy, precision, and recall. Additionally, the classification program assists medical professionals in determining optimal treatment plans and predicting patient recurrence rates and survival probabilities through regression analysis and risk stratification algorithms. Therefore, this breast cancer classification program serves as a vital medical tool that enhances patient care through data-driven decision support.