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September 29, 2025Open Access

Multimodal Imaging and Logistic Weighted Cognitive Scores for Classification of MCI, AD, and FTD Subtypes

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Authors

SKSunil Kumar KhokharRMRohit MisraMKManoj Kumar

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Overview

Analysis shows enhanced classification accuracy for MCI and dementia using multimodal imaging, highlighting its potential benefits.

Key Points

  • The model achieved 83% accuracy differentiating between MCI and dementia, including AD and FTD.
  • Classification accuracies reached 87% for MCI vs. PPA and 64% for MCI vs. AD, indicating significant discriminative ability.
  • A Naive Bayes classifier integrated cortical thickness and FDG-PET features to enhance diagnostic precision for dementia subtypes.
  • Findings suggest integrating ACE-III scores with neuroimaging could improve early-stage differentiation of dementia variants.

Cite This Study

Khokhar et al. (2025) studied this question.

synapsesocial.com/papers/68da58dcc1728099cfd11320https://doi.org/10.1101/2025.09.27.678895
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