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November 18, 2025npj Parkinson s Disease0 citationsOpen Access

Prediction model for mild cognitive impairment in Parkinson’s disease using multimodal data

Construction of a mild cognitive impairment prediction model for Parkinson’s disease patients on the basis of multimodal data

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Authors

CLChun-Yu LiangYCYili ChenYZYongyun Zhu

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Overview

Research demonstrates a prediction model for mild cognitive impairment in Parkinson’s disease patients using multimodal data, highlighting the role of machine learning.

Key Points

  • To develop a model predicting mild cognitive impairment in Parkinson's disease patients using multimodal indicators.
  • Prospective collection of data from PDMCI, PDNC, and HC groups
  • Utilization of clinical scales, gait, eye tracking, and neuroimaging parameters
  • Application of Support Vector Machine classifiers and nested cross-validation
  • Achieved average accuracy of 0.9135
  • Average area under the curve of 0.9602 on the test dataset
  • Combination of eye tracking and gait features showed superior performance

Cite This Study

Liang et al. (2025) studied this question.

synapsesocial.com/papers/6924fee0c0ce034ddc3515a8https://doi.org/10.1038/s41531-025-01172-z
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