The Role of AI in Predicting and Managing Chronic Diseases

Abstract

Chronic illness, such as renal or heart disease, is now ranked among the main causes of mortality globally. Preventing chronic illness is a very difficult endeavour. Only chronic sickness may be predicted by medical professionals who have experience and knowledge with this illness. The Internet of Things (IoT) is a critical piece of technology in a healthcare system. This research proposes the EO-LWAMCNet model, an EO optimized Lighter Automatic modulator classification network, to reliably predict a patient's chronic health status (heart or kidney illness). The term "edge AI" refers to artificial intelligence (AI) and data analytics that use federated learning, deep learning, and deep learning models that are implemented and run at the network's edge, away from centralized data centres. Artificial Intelligence (AI) facilitates the meticulous examination of extensive datasets that come from many sources, including as wearable technology, demographic data, and digital health records. This allows for the identification of complex trends and predictions of an individual's future health