Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.

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 in home settings with descriptions of PD facial expressions, in identifying patients with PD.

Methods

Facial image of 67 PD patients and 52 healthy-controls (HCs) were collected via standard video recording. Using clinical knowledge, we compiled descriptive sentences detailing facial characteristics associated with PD. The facial images were analyzed with OpenAI's CLIP model to gene

SUBMITTER: Rom H 

PROVIDER: S-EPMC12329937 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature