KIDNEY DISEASE PREDICTION MODEL USING AN EXPERT SYSTEM
Abstract
Kidney disease affects millions globally, and early diagnosis is crucial for effective treatment. This project aims to develop a kidney disease prediction model using an expert system integrated with a Support Vector Machine (SVM) classifier. The system processes patient symptoms and medical records to assist in diagnosing kidney diseases. The model is trained using a dataset, with 70% allocated for training and 30% for testing, ensuring reliable performance. A user-friendly interface, implemented using the Flask framework, allows healthcare professionals to input patient data and receive diagnostic results. By leveraging AI, the system enhances diagnostic accuracy, offering a reliable tool for improving patient outcomes and supporting clinical decision-making.
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