Machine Learning and Geospatial Specialist Mapping-based Severe Disease Prediction System

Abstract

In the traditional healthcare system, early detection/diagnosis of diseases is a major concern, especially when it comes to chronic and life-threatening diseases. Although common disease conditions can be fluently diagnosed and treated on time, severe disease conditions need to be diagnosed earlier to ensure effective treatment. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have significantly improved the accuracy of disease prediction and supported better clinical decision-making. However, most existing ML-based predictive models are developed to detect or predict only a single specific disease profile. They cannot usually analyse and predict multiple diseases within a single integrated system. This study presents an advanced AI-ML integrated disease prediction platform that can diagnose both common and severe disease conditions on a single platform. The proposed platform integrates multiple machine learning models for different disease conditions into a single platform, divided into separate sections according to complaint types. The platform also enhances usability by recommending suitable medical specialists according to the complaint based on the user’s geographical location, therefore providing timely medical consultation. The proposed frame, which combines lifestyle, symptom and medical history-based diagnosing algorithms, is a scalable and doable result for the current digital healthcare system.