ARTIFICIAL INTELLIGENCE AND DIGITAL BIOMARKERS IN THE EARLY DIAGNOSIS AND PREDICTION OF PARKINSON'S DISEASE: A SYSTEMATIC REVIEW (2020–2025)
Authors/Creators
- 1. Fergana Medical Institute of Public Health Department of "Biomedical Engineering
- 2. Biophysics and Information Technologies" Assistant Lecturer
- 3. 1st year, Faculty of General Medicine Fergana Medical Institute of Public Health Uzbekistan,Student, 1st year, Faculty of General Medicine Fergana Medical Institute of Public Health Uzbekistan
Description
According to data from the STADA Health Report 2023, the disease that people in Uzbekistan fear the most is Parkinson's disease. This disease causes concern among 23% of the country’s population. These fears are not unfounded, as the disease is considered the second most common neurodegenerative disorder worldwide.
Parkinson’s disease is a condition caused by a deficiency of dopamine-producing neurons in the substantia nigra, which manifests itself through movement disorders.
This article presents various methods of applying artificial intelligence and digital biomarkers for the diagnosis of Parkinson’s disease. It discusses the possibility of early diagnosis of Parkinson’s disease using artificial intelligence methods.
The paper proposes an approach for detecting the disease using video analysis of a patient’s smile as a digital biomarker, an artificial intelligence model for diagnosing Parkinson’s disease based on frequency anomalies in electroencephalography (EEG), and automatic early detection of Parkinson’s disease through the analysis of acoustic signals using classification algorithms based on the Recursive Feature Elimination (RFE) method.
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Additional details
References
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