Peer-Reviewed Publication
BMC Med Inform Decis Mak2025;25(1):294.August 7, 2025Journal Article
Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.
Harel Rom1,2, Ori Peleg1,3, Yovel Rom4, Anat Mirelman1,2,3, Gaddi Blumrosen5,6, Inbal Maidan7,8,9
1Laboratory of Early Markers of Neurodegeneration, Neurological Institute, Tel Aviv Sourasky Medical Center, 6 Weizmann Street, Tel Aviv, 64239, Israel.
2Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
3Gray Faculty of Medical and Health Sciences, Tel Aviv University, Tel-Aviv, Israel.
4AEYE Health, Tel Aviv, Israel.
5Faculty of Digital Medical Technologies, Holon Institute of Technology (HIT), Holon, Israel.
6School of Computer Science, Holon Institute of Technology (HIT), Holon, Israel.
7Laboratory of Early Markers of Neurodegeneration, Neurological Institute, Tel Aviv Sourasky Medical Center, 6 Weizmann Street, Tel Aviv, 64239, Israel. inbalm@tlvmc.gov.il.
8Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel. inbalm@tlvmc.gov.il.
9Gray Faculty of Medical and Health Sciences, Tel Aviv University, Tel-Aviv, Israel. inbalm@tlvmc.gov.il.
Abstract
BACKGROUND: Early diagnosis of Parkinson's disease (PD) can assist in designing efficient treatments. Reduced facial expressions are considered a hallmark of PD, making advanced artificial intelligence (AI) image processing a potential non-invasive clinical decision support tool for PD detection. This study aims to determine the sensitivity of image-to-text AI, which matches facial frames recorded…
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