Multiple-Disease-Prediction-Using-Machine-Learning

A Multiple Disease Prediction System is designed to provide early detection and diagnosis of multiple diseases. Testing such a system requires a rigorous evaluation process to ensure its accuracy and effectiveness. The first step in testing would be to gather a dataset of patients with various symptoms and conditions, along with their corresponding diagnoses. This data would be used to train the system and test its ability to accurately predict the likelihood of multiple diseases. The system's performance would be evaluated using metrics such as sensitivity, specificity, and accuracy. Once the system has been thoroughly tested and validated, it can be implemented in clinical settings to assist healthcare professionals in making accurate and timely diagnoses, ultimately improving patient outcomes.