Prediction of future dementia among patients with mild cognitive impairment (MCI) by integrating multimodal clinical data.

ABSTRACT: Efficiently and objectively analyzing the complex, diverse multimodal data collected from patients at risk for dementia can be difficult in the clinical setting, contributing to high rates of underdiagnosis or misdiagnosis of this serious disorder. Patients with mild cognitive impairment (MCI) are especially at risk of developing dementia in the future. This study evaluated the ability of multi-modal machine learning (ML) methods, especially the Ensemble Integration (EI) framework, to predict future dementia development among patients with MCI. EI is a machine learning framework designed to leverage complementarity and consensus in multimodal data, which may not be adequately captured by methods used by prior dementia-related prediction studies. We tested EI's ability to predict future dem

SUBMITTER: Cirincione A 

PROVIDER: S-EPMC11399681 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature