TY  - JOUR
AU  - Hedderich, Dennis M.
AU  - Eickhoff, Simon
TI  - Machine learning for psychiatry: getting doctors at the black box?
JO  - Molecular psychiatry
VL  - 26
SN  - 1476-5578
CY  - London
PB  - Macmillan
M1  - FZJ-2020-04515
SP  - 23-25
PY  - 2021
AB  - Recent developments in the field of machine-learning have spurred high hopes for diagnostic support for psychiatric patients based on brain MRI. But while technical advances are undoubtedly remarkable, the current trajectory of mostly proof-of-concept studies performed on retrospective, often repository-derived data, may not be well suited to yield a substantial impact in clinical practice. Here we review these developments and challenges, arguing for the need of stronger involvement of and input from medical doctors in order to pave the way for machine-learning in clinical psychiatry.
LB  - PUB:(DE-HGF)16
C6  - 33173196
UR  - <Go to ISI:>//WOS:000588233100003
DO  - DOI:10.1038/s41380-020-00931-z
UR  - https://juser.fz-juelich.de/record/887913
ER  -