| Evaluating the evidence for biotypes of depression: Methodological replication and extension of R Dinga, L Schmaal, BWJH Penninx, MJ van Tol, DJ Veltman, ... NeuroImage: Clinical 22, 101796, 2019 | 265 | 2019 |
| Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group LKM Han, R Dinga, T Hahn, CRK Ching, LT Eyler, L Aftanas, M Aghajani, ... Molecular psychiatry 26 (9), 5124-5139, 2021 | 175 | 2021 |
| From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder T Wolfers, DL Floris, R Dinga, D van Rooij, C Isakoglou, SM Kia, M Zabihi, ... Neuroscience & Biobehavioral Reviews 104, 240-254, 2019 | 116 | 2019 |
| Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach R Dinga, AF Marquand, DJ Veltman, ATF Beekman, RA Schoevers, ... Translational psychiatry 8 (1), 241, 2018 | 110 | 2018 |
| The normative modeling framework for computational psychiatry S Rutherford, SM Kia, T Wolfers, C Fraza, M Zabihi, R Dinga, P Berthet, ... Nature protocols 17 (7), 1711-1734, 2022 | 83 | 2022 |
| Charting brain growth and aging at high spatial precision S Rutherford, C Fraza, R Dinga, SM Kia, T Wolfers, M Zabihi, P Berthet, ... elife 11, e72904, 2022 | 75 | 2022 |
| Subcortical shape alterations in major depressive disorder: Findings from the ENIGMA major depressive disorder working group TC Ho, B Gutman, E Pozzi, HJ Grabe, N Hosten, K Wittfeld, H Völzke, ... Human brain mapping 43 (1), 341-351, 2022 | 73 | 2022 |
| Controlling for effects of confounding variables on machine learning predictions R Dinga, L Schmaal, BWJH Penninx, DJ Veltman, AF Marquand BioRxiv, 2020.08. 17.255034, 2020 | 67 | 2020 |
| Beyond accuracy: Measures for assessing machine learning models, pitfalls and guidelines R Dinga, BWJH Penninx, DJ Veltman, L Schmaal, AF Marquand BioRxiv, 743138, 2019 | 57 | 2019 |
| Warped Bayesian linear regression for normative modelling of big data CJ Fraza, R Dinga, CF Beckmann, AF Marquand NeuroImage 245, 118715, 2021 | 48 | 2021 |
| Hierarchical Bayesian regression for multi-site normative modeling of neuroimaging data SM Kia, H Huijsdens, R Dinga, T Wolfers, M Mennes, OA Andreassen, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 46 | 2020 |
| Predicting individual clinical trajectories of depression with generative embedding S Frässle, AF Marquand, L Schmaal, R Dinga, DJ Veltman, ... NeuroImage: Clinical 26, 102213, 2020 | 43 | 2020 |
| Default mode network connectivity and social dysfunction in major depressive disorder IMJ Saris, BWJH Penninx, R Dinga, MJ van Tol, DJ Veltman, ... Scientific reports 10 (1), 194, 2020 | 39 | 2020 |
| Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models JMM Bayer, R Dinga, SM Kia, AR Kottaram, T Wolfers, J Lv, A Zalesky, ... Neuroimage 264, 119699, 2022 | 33 | 2022 |
| Normative modeling of neuroimaging data using generalized additive models of location scale and shape R Dinga, CJ Fraza, JMM Bayer, SM Kia, CF Beckmann, AF Marquand BioRxiv, 2021.06. 14.448106, 2021 | 29 | 2021 |
| High-resolution 7-Tesla fMRI data on the perception of musical genres – an extension to the studyforrest dataset M Hanke, R Dinga, C Häusler, JS Guntupalli, M Casey, FR Kaule, ... F1000Research 4, 174, 2015 | 29 | 2015 |
| Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates YJ Toenders, L Schmaal, BJ Harrison, R Dinga, M Berk, CG Davey Translational Psychiatry 10 (1), 108, 2020 | 25 | 2020 |
| Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression SM Kia, H Huijsdens, S Rutherford, A de Boer, R Dinga, T Wolfers, ... Plos one 17 (12), e0278776, 2022 | 22 | 2022 |
| Federated multi-site normative modeling using hierarchical Bayesian regression SM Kia, H Huijsdens, S Rutherford, R Dinga, T Wolfers, M Mennes, ... BioRxiv, 2021.05. 28.446120, 2021 | 21 | 2021 |
| Predicting depression onset in young people based on clinical, cognitive, environmental, and neurobiological data YJ Toenders, A Kottaram, R Dinga, CG Davey, T Banaschewski, ... Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 7 (4), 376-384, 2022 | 16 | 2022 |
Andre F MarquandProfessor of Computational Psychiatry, Donders Institute / Kings College LondonVerified email at kcl.ac.uk
