Mobile Health Solutions for Effective Symptom Detection and Disease Management Using Machine Learning

People in today's world are so busy with work and other commitments that they rarely have time to see doctors for illnesses that initially seem minor but eventually become life-threatening. In the above situations, where patients do not have easy access to healthcare or face difficulties in utilizing it, this can be very useful in helping them understand the urgency of their health condition. The suggested algorithm makes use of machine learning to forecast diseases based on user-provided symptoms. The flow of the disease diagnosis support system using symptoms is as follows: First, data pre-processing is performed, and several machine learning classification models, including K Nearest Neighbor, are then applied to the data, Random Forest, and Support Vector Machine (SVM). The accuracy of each model is calculated to aid in predicting the disease based on the mentioned symptoms. The predicted disease is then sent back to the application, where it is displayed to the user. Our model primarily focuses on seasonal infections and diseases.