Machine Learning Algorithms to Enhance The Performance of PD Prediction

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Published: Sep 1, 2023
DOI: https://doi.org/10.29070/de54jn83
Keywords:
Machine Learning, Algorithms, Prediction, computers

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Authors

Lakshmikant Bopche

Research Scholar, Shridhar University, Pillani, Rajasthan

Dr. D. S. Bhangari

Professor, Shridhar University, Pillani, Rajasthan

Abstract

Deep learning's strong performance and capacity to learn features automatically have propelled it into the AI mainstream in recent years, where it is being used in a wide variety of applications. In certain fields, like medicine, deep learning may outperform human physicians in terms of accuracy. neurodegenerative diseases, especially Alzheimer's disease, affecting neurons. Tremors, stiffness, and decreased balance are classic motor symptoms of Parkinson's disease, which is caused by a depletion of dopamine neurons in the brain. This disruption in smooth coordination and communication with other nerve cells makes the condition more difficult to control. One of the hallmark clinical aspects of Parkinson's disease is a decline in motor coordination, which shows the central role of dopamine in controlling movement. Motor and non-motor symptoms are also affected by a lack of dopamine neurons. Manual symptom checking is still used to identify Parkinson's disease by doctors and other medical professionals. Researchers have proposed a plethora of ways for Parkinson's disease diagnosis. Voice signals, handwriting traces, MRIs, PET/SPECT scans, and a battery of other modalities are all part of the toolbox for these techniques. Patients with the condition now have improved alternatives for managing symptoms, even though there is no proven medicine to change the illness.

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Issue

Vol. 20 No. 2 (2023): Journal of Advances in Science and Technology (JAST)

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