Prediction of Alzheimer's disease dementia with MRI beyond the short-term: Implications for the design of predictive models.

ABSTRACT: Magnetic resonance imaging (MRI) volumetric measures have become a standard tool for the detection of incipient Alzheimer's Disease (AD) dementia in mild cognitive impairment (MCI). Focused on providing an earlier and more accurate diagnosis, sophisticated MRI machine learning algorithms have been developed over the recent years, most of them learning their non-disease patterns from MCI that remained stable over 2-3 years. In this work, we analyzed whether these stable MCI over short-term periods are actually appropriate training examples of non-disease patterns. To this aim, we compared the diagnosis of MCI patients at 2 and 5 years of follow-up and investigated its impact on the predictive performance of baseline volumetric MRI measures primarily involved in AD, i.e., hippocampal and ent

SUBMITTER: Moscoso A 

PROVIDER: S-EPMC6515129 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature