Augmented and Virtual Reality in Immersive Healthcare

9Machine Learning–Based Disease Diagnosis and Treatment in Healthcare: A Review and Evaluation

Chandrashekhar Bechoo and Avinash Mungur^*

Department of Information and Communication Technologies (ICT), Faculty of Information, Communication and Technologies (FoICDT), University of Mauritius, Reduit, Mauritius

Abstract

In healthcare, proper treatment and disease diagnosis are both critical, mainly due to the intrinsic nature of the disease mechanisms and the symptoms among the patients. The traditional diagnostic methods involve making use of the historical records of an individual and performing multiple medical tests. However, the most common problem of traditional diagnostic methods is that they could lead to either overdiagnosis or misdiagnosis, which significantly affects the life of the medical patient by following unnecessary treatments. In recent years, machine learning (ML) has become an important tool in healthcare contributing to early detection of diseases with high accuracy and efficiency. This chapter examines recent academic papers on ML-based disease diagnosis (MLBDD), mainly focusing on five significant diseases that are breast cancer, diabetes, COVID-19, heart disease, and Parkinson’s disease (PD). These identified diseases have considerably affected the public health in Mauritius. Diabetes is a severe metabolic disorder that significantly impacts the Mauritian adult population together with heart disease, which remains the driving cause of death, highlighting ...