RT Journal Article
T1 Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia
A1 Facal Mayo, David
A1 Valladares Rodríguez, Sonia María
A1 Lojo Seoane, Cristina
A1 Pereiro Rozas, Arturo X.
A1 Anido Rifón, Luis
A1 Juncos Rabadán, Onésimo
K1 Cognitive reserve
K1 Dementia
K1 Diagnostic transitions
K1 Educational level
K1 Gradient boosting classifier
K1 Machine learning
K1 Mild cognitive impairment
K1 Random forest classifier
K1 Supervised learning
K1 Vocabulary
AB Objectives: The overall aim of the present study was to explore the role of cognitive reserve (CR) in the conversion from mild cognitive impairment (MCI) to dementia. We used traditional and machine learning (ML) techniques to compare converter and nonconverter participants. We also discuss the predictive value of CR proxies in relation to the ML model performance. Methods: In total, 169 participants completed the longitudinal study. Participants were divided into a control group and three MCI subgroups, according to the Petersen criteria for diagnosis. Information about the participants was compared using nine ML classification techniques. Seven relevant performance metrics were computed in order to evaluate the accuracy of prediction regarding converter and nonconverter participants. Results: ML algorithms applied to socio‐demographic, basic health, and CR proxy data enabled prediction of conversion to dementia. The best performing models were the gradient boosting classifier (accuracy (ACC) = 0.93; F1 = 0.86, and Cohen κ = 0.82) and random forest classifier (ACC = 0.92; F1 = 0.79, and Cohen κ = 0.71). Use of ML techniques corroborated the protective role of CR as a mediator of conversion to dementia, whereby participants with more years of education and higher vocabulary scores survived longer without developing dementia. Conclusions: We used ML approaches to explore the role of CR in conversion from MCI to dementia. The findings indicate the potential value of ML algorithms for detecting risk of conversion to dementia in cognitive aging and CR studies. Further research is required to develop an ML‐based procedure that can be used to make robust predictions.
PB Online Library Wiley
SN 0885-6230
YR 2019
FD 2019-03-10
LK https://hdl.handle.net/10347/38974
UL https://hdl.handle.net/10347/38974
LA eng
NO Facal, D., Valladares‐Rodriguez, S., Lojo‐Seoane, C., Pereiro, A. X., Anido‐Rifon, L., & Juncos‐Rabadán, O. (2019). Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia. International journal of geriatric psychiatry, 34(7), 941-949.
DS Minerva
RD 24 abr 2026