Open AccessMachine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: A systematic review
Author(s) -
Pellegrini Enrico,
Ballerini Lucia,
Hernandez Maria del C. Valdes,
Chappell Francesca M.,
GonzálezCastro Victor,
Anblagan Devasuda,
Danso Samuel,
MuñozManiega Susana,
Job Dominic,
Pernet Cyril,
Mair Grant,
MacGillivray Tom J.,
Trucco Emanuele,
Wardlaw Joanna M.
Publication year - 2018
Publication title -
alzheimer's and dementia: diagnosis, assessment and disease monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.497
H-Index - 37
ISSN - 2352-8729
DOI - 10.1016/j.dadm.2018.07.004
Subject(s) - dementia , neuroimaging , disease , cognition , machine learning , artificial intelligence , alzheimer's disease neuroimaging initiative , support vector machine , cognitive impairment , alzheimer's disease , psychology , medicine , computer science , neuroscience , pathology
Advanced machine learning methods might help to identify dementia risk from neuroimaging, but their accuracy to date is unclear. Methods We systematically reviewed the literature, 2006 to late 2016, for machine learning studies differentiating healthy aging from dementia of various types, assessing study quality, and comparing accuracy at different disease boundaries. Results Of 111 relevant studies, most assessed Alzheimer's disease versus healthy controls, using AD Neuroimaging Initiative data, support vector machines, and only T1‐weighted sequences. Accuracy was highest for differentiating Alzheimer's disease from healthy controls and poor for differentiating healthy controls versus mild cognitive impairment versus Alzheimer's disease or mild cognitive impairment converters versus nonconverters. Accuracy increased using combined data types, but not by data source, sample size, or machine learning method. Discussion Machine learning does not differentiate clinically relevant disease categories yet. More diverse data sets, combinations of different types of data, and close clinical integration of machine learning would help to advance the field.