Detalhe da pesquisa
1.
Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder.
Mol Psychiatry
; 28(3): 1057-1063, 2023 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-36639510
2.
From 'loose fitting' to high-performance, uncertainty-aware brain-age modelling.
Brain
; 144(3): e31, 2021 04 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-33826702
3.
A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder.
JAMA Psychiatry
; 81(4): 386-395, 2024 Apr 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-38198165
4.
Towards a network control theory of electroconvulsive therapy response.
PNAS Nexus
; 2(2): pgad032, 2023 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-36874281
5.
Seizure Prediction in Genetic Rat Models of Absence Epilepsy: Improved Performance through Multiple-Site Cortico-Thalamic Recordings Combined with Machine Learning.
eNeuro
; 9(1)2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-34782347
6.
An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling.
Sci Adv
; 8(1): eabg9471, 2022 Jan 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-34985964
7.
Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder Across Neuroimaging Modalities.
JAMA Psychiatry
; 79(9): 879-888, 2022 09 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-35895072
8.
PHOTONAI-A Python API for rapid machine learning model development.
PLoS One
; 16(7): e0254062, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34288935