Sia et al. (2024) developed an AI-based disease prediction chatbot system with a promising accuracy result of 90%. They used four machine learning algorithms to build a prediction model that can recognize potential diseases based on reported symptoms. Here is the performance of each algorithm: Table 1. Performance of machine learning algorithms in the disease...Read More

Assegie et al. (2022) explored a dataset of heart disease images using machine learning models to predict heart disease. They used recursive feature elimination with cross-validation (RFECV) to analyze the significance of heart disease features on the output generated by the model. The dataset for this experiment was obtained from the University of California Irvine...Read More