Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach.

ABSTRACT: Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional measures and increase diagnostic confidence. Yet, widespread application of these tools cannot be recommended unless they are proven to perform consistently and reproducibly across samples from different countries. We implemented machine-learning algorithms to evaluate the prediction power of neurocognitive biomarkers (behavioral and imaging measures) for classifying two neurodegenerative conditions -Alzheimer Disease (AD) and behavioral variant frontotemporal dementia (bvFTD)- across three different countries (>200 participants). We use machine-le

SUBMITTER: Bachli MB 

PROVIDER: S-EPMC7008715 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature