Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging.

ABSTRACT: Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating individual differences in various behavioral phenotypes and clinical outcomes is of growing interest. However, the field is experiencing challenges regarding the interpretability of the results. Approaches to defining the specific contribution of functional connections, regions, or networks in prediction models are urgently needed, which may help explore the underlying mechanisms. In this article, we systematically review the methods and applications for interpreting brain signatures derived from predictive neuroimaging based on a survey of 326 research articles. Strengths, limitations, and the suitable conditions for major interpretation strategies are also deliberated. In-depth discussion of common issues i

SUBMITTER: Jiang R 

PROVIDER: S-EPMC9880880 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature