TY  - JOUR
AU  - Gorriz, J. M.
AU  - Martin-Clemente, R.
AU  - Puntonet, C. G.
AU  - Ortiz, A.
AU  - Ramirez, J.
AU  - Suckling, J.
PY  - 2022
DO  - 10.1016/j.neucom.2022.09.001
SN  - 0925-2312
UR  - http://hdl.handle.net/10668/22421
T2  - Neurocomputing
AB  - There remains an open question about the usefulness and the interpretation of machine learning (ML) approaches for discrimination of spatial patterns of brain images between samples or activation states. In the last few decades, these approaches have...
LA  - en
PB  - Elsevier BV
KW  - General Linear Model
KW  - Linear Regression Model
KW  - Support Vector Regression
KW  - permutation tests
KW  - Magnetic Resonance Imaging
KW  - Random Field Theory
KW  - Support vector machine
KW  - Functional mri
KW  - Diagnosis
KW  - Framework
KW  - Linear Models
KW  - Benchmarking
KW  - Research Design
KW  - Brain
KW  - Machine Learning
TI  - A hypothesis-driven method based on machine learning for neuroimaging data analysis
TY  - research article
VL  - 510
ER  -