A Computer-Aided Prediagnosis System for Health Prediction Based on Personal Health Data

In this era of telemedicine, the effectiveness of healthcare services is enhanced by prediagnosis based on some common health parameters. The doctor’s expertise and experience inform every clinical choice in the traditional healthcare system. Although this common technique may look reasonable at first glance, it might potentially result in unanticipated mistakes, biases, and maximized expenses, all of which could have an adverse effect on the QoS (Quality-of-Service) provided to patients. The traditional method of data analysis and prediagnosis system for clinical-decision support has to be modernized so that medical professionals may save more time. Actually, the rural parts of India still lag in the health care system as people are less aware of the disease and its precaution and suffer the most due to lack of information. In this proposed method, a computer-aided pre-diagnosis system has been designed based on machine learning (ML) algorithms that require some basic health parameters gives a correct health status of a person. A Graphical user interface (GUI) is introduced for users to enter their health data or medical values to predict their health condition. Based on the results, the user may get in touch with a doctor or nurse through their preferred mode. Moreover, it is an age-free application, i.e., it could be applicable to people of all age groups. An extensive comparison of different ML algorithms is done on real-time medical data, and it is found that support vector machine gives the best results.