Machine Learning-Based Disease Diagnosis Using Body Signals: A Review

Effective illness diagnosis is an unmet clinical need on a global scale. Building a tool for early diagnosis and an efficient course of treatment is particularly challenging due to the complexity of many complex diseases and core symptoms of the patient group. Some of these problems can be resolved by researchers, doctors, and patients thanks to machine learning (ML), a branch of artificial intelligence (AI). Based on relevant research, this review describes the use of machine learning in the early identification of several diseases. The paper then provides a summary of the most recent developments in the field of machine learning-based disease detection and telemedicine, taking into account the algorithm, various disease kinds, various body signals, various applications, and various assessment metrics. Finally, we summarize the main results and provide some perspective on possible future trends and research directions.