AI-BASED UTERUS CANCER RISK PREDICTION AND DECISION SUPPORT SYSTEM USING MACHINE LEARNING

The proposed AI-Based Uterus Cancer Risk Prediction System provides a web-based approach for preliminary cancer risk assessment using patient-related information and machine learning techniques. The system integrates data preprocessing, AI-based prediction, risk classification, recommendation generation, and prediction-history management into a single platform. The developed application provides users with a simple interface for entering relevant information and receiving a prediction with its corresponding confidence and risk category. The integration of recommendations and historical records further improves the usefulness of the system as a decision-support and health-awareness tool. The proposed approach demonstrates the potential of artificial intelligence to assist in the early assessment of cancer-related risk. However, the system should be considered a supportive tool rather than a replacement for clinical diagnosis. The reliability of the results depends on the quality and diversity of the dataset used for model development. Future work can focus on larger clinically validated datasets, improved model architectures, extensive external validation, and integration of explainable AI techniques to make predictions more transparent and clinically interpretable [37][38].  

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