The Role of Artificial Intelligence and Machine Learning in Parkinson's Disease Diagnosis and Atypical Parkinsonisms

This literature review examines how machine learning techniques, particularly support vector machines and neural networks, can improve early diagnosis and progression prediction in Parkinson's disease by analyzing diverse biomarker data. The analysis demonstrates that more sophisticated machine learning approaches and ensemble models achieve higher diagnostic accuracy than simpler methods, suggesting significant potential for enhancing diagnostic capacity in movement disorders.