• BALVINDER KAUR
• MEENAKSHI GUPTA
• RENU VADHERA

Parkinson's Disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms that significantly impair quality of life. Early detection and accurate diagnosis of PD remain critical challenges due to the complexity of its symptoms and the overlapping characteristics with other neurological disorders. Artificial Intelligence (AI) has emerged as a powerful tool in medical diagnosis, particularly through the application of Machine Learning (ML) and Deep Learning (DL) techniques. This comprehensive review explores the advancements in AI-based approaches for detecting and diagnosing Parkinson's Disease, focusing on various ML algorithms and DL architectures used in image processing, voice analysis, gait assessment, and biomarker identification. The review highlights the strengths and limitations of different models, such as Support Vector Machines (SVM), Random Forests, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs), in classifying PD and predicting disease progression. Furthermore, it discusses the challenges in data acquisition, feature selection, and the need for large, diverse datasets to improve model generalizability. The integration of AI into clinical practice holds promising potential for enhancing diagnostic accuracy, reducing the burden of manual assessments, and providing personalized treatment strategies for Parkinson's patients.

Parkinson's Disease detection, Artificial Intelligence(AI), Machine Learning(ML), Deep Learning(DP), Convolutional Neural Networks(CNN), Support Vector Machines(SVM), Recurrent Neural Networks(RNN), brain imaging, gait analysis, speech analysis , biomarkers, neurodegenerative disorders,

"Artificial Intelligence in Parkinson's disease detection: A Comprehensive review of Machine learning and deep learning approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.e518-e526, December-2024, Available :http://www.jetir.org/papers/JETIR2412459.pdf

"Artificial Intelligence in Parkinson's disease detection: A Comprehensive review of Machine learning and deep learning approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppe518-e526, December-2024, Available at : http://www.jetir.org/papers/JETIR2412459.pdf