Liver Disorder Diagnosis using Comparative Machine Learning Techniques

Liver diseases represent a significant global health concern, with millions of individuals affected by various liver conditions worldwide. Early and accurate diagnosis is crucial for effective treatment and improved patient outcomes. In this context, we present the development of an AI-based Liver Disease Detector, a novel and innovative approach to assist healthcare professionals in diagnosing liver diseases. Our Liver Disease Detector leverages cutting-edge artificial intelligence techniques, including deep learning algorithms, to analyze medical data such as liver function tests, imaging scans, and patient histories. Through a comprehensive analysis of these data points, our system can identify patterns, anomalies, and potential indicators of liver diseases. For this project, ensemble technique is employed to combine the results obtained from Artificial NN, Support Vector Machine and Random Forest