A Systematic Review of Artificial Intelligence (AI) Based Approaches for the Diagnosis of Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder that primarily affects the elderly for over 55 years. PD can be characterised by patients exhibiting various non-motor and motor symptoms. It is significant to note that even though modern-day medical technology has grown exponentially over the years, there is still no cure for Parkinson's disease. Hence, it is a scientifically exciting proposal to develop technologies that diagnose Parkinson's disease earlier. Early diagnosis of PD can enhance the patient's quality of life to a reasonable extent, as the disease's nature is progressive, and it may take years to cripple the patient. It is also essential to observe that the symptoms will get intensified over time. Early diagnosis can also predict other types of neurodegenerative diseases, as the symptoms are pretty similar. The idea of Artificial Intelligence (AI) techniques is recently getting significant medical diagnosis attention, as these technologies can process massive data and come up with good statistical predictions. This study presents a detailed review of various machine learning and deep learning-based AI techniques applied to PD diagnosis and their impact in opening up newer research avenues. Furthermore, this paper explores the possible opportunities of data-driven AI technologies in PD diagnosis and its current status. [ABSTRACT FROM AUTHOR]