AI Cancer Prediction System

This paper presents an AI-based cancer prediction system using ensemble machine learning techniques. The proposed approach integrates multiple classifiers including Random Forest, Gradient Boosting, Support Vector Machine, Multi-Layer Perceptron, and Logistic Regression to improve prediction accuracy and robustness.

The system is evaluated using publicly available, de-identified medical datasets and standard performance metrics such as accuracy, precision, recall, and ROC-AUC. Explainable AI techniques are incorporated to enhance model interpretability. This work is shared as an open-access preprint for academic and research dissemination.