Dong-A University Department of Health Sciences Master’s Student Hwang Juseon Publishes Paper in International Multidisciplinary Science Journal

Early Detection and Objective Assessment of Parkinson’s Disease Progression
Potential for Optimizing Treatment and Rehabilitation for Parkinson’s Disease Patients

Dong-A University (President Lee Hae-woo) announced on the 16th that graduate student Hwang Ju-seon (graduate of the Department of Health Management), who is currently enrolled in the master's program in the Department of Health Sciences, has published a paper as the first author in the internationally renowned multidisciplinary science journal, Scientific Reports.

Scientific Reports, an SCI-level international journal, is a globally prestigious journal in the field of Multidisciplinary Sciences, ranking in the top 18.3% in JCR, with an impact factor of 3.8.

From the left, Hwang Juseon, a master's student in the Department of Health Science at Dong-A University, and Yeom Changhong, the supervising professor. Provided by Dong-A University

The paper by Dong-A University master's student Hwang Ju-seon is titled "Machine Learning for Early Detection and Severity Classification in People with Parkinson’s Disease (doi.org/10.1038/s41598-024-83975-3)" and focuses on the early detection and objective evaluation of disease progression of Parkinson’s disease, one of the representative progressive neurodegenerative diseases whose incidence is rapidly increasing alongside an aging society.

Supported by the Korea Research Foundation’s Mid-Career Research Program and the Ministry of Education’s 4th phase BK21 project, the results of this study are expected to be crucial in optimizing treatment and rehabilitation for Parkinson’s disease patients.

Parkinson’s disease causes the loss of dopamine neurons in the substantia nigra of the midbrain, disrupting the function of the basal ganglia circuit and impairing motor control, leading to a decline in the ability to perform automated movements such as walking. This results in severe movement disorders, loss of independence in daily life, and a decrease in quality of life, making early management extremely important.

This study identified digital biomarkers capable of early diagnosis and severity classification of Parkinson’s disease, evaluated the accuracy of machine learning model-based classification, and achieved improvements in classification accuracy through the research process.

Master’s student Hwang Ju-seon said, “Thanks to the unwavering support and guidance from Professor Yeom Chang-hong of the Department of Health Sciences and seniors in the Biomechanics Laboratory, who helped lay the foundation for me as a researcher, I was able to achieve good results. I want to continue research related to developing early diagnosis and severity classification models for Parkinson’s disease patients, as well as customized home-based digital intervention and treatment programs, to help improve treatment strategies and physical function for patients.”

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