Richard Dinga
Richard Dinga
Postdoc, Donders Institute
Overená e-mailová adresa na:
Citované v
Citované v
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
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, 1-16, 2020
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), 1-11, 2018
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
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), 174, 2015
Beyond accuracy: Measures for assessing machine learning models, pitfalls and guidelines
R Dinga, BWJH Penninx, DJ Veltman, L Schmaal, AF Marquand
bioRxiv, 743138, 2019
Predicting individual clinical trajectories of depression with generative embedding
S Frässle, AF Marquand, L Schmaal, R Dinga, DJ Veltman, ...
NeuroImage: Clinical 26, 102213, 2020
Controlling for effects of confounding variables on machine learning predictions
R Dinga, L Schmaal, BWJH Penninx, DJ Veltman, AF Marquand
BioRxiv, 2020
Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data
SM Kia, H Huijsdens, R Dinga, T Wolfers, M Mennes, OA Andreassen, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2020
A closer look at depression biotypes: Correspondence relating to Grosenick et al.(2019)
R Dinga, L Schmaal, AF Marquand
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 5 (5), 554-555, 2020
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), 1-11, 2020
Phenomapping: Methods and measures for deconstructing diagnosis in psychiatry
AF Marquand, T Wolfers, R Dinga
Personalized Psychiatry, 119-134, 2019
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, ...
bioRxiv, 2021
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), 1-11, 2020
Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group. bioRxiv [pre-print]. 2019; 1–33
LK Han, R Dinga, T Hahn
Publisher Full Text, 0
Warped bayesian linear regression for normative modelling of big data
C Fraza, R Dinga, CF Beckmann, AF Marquand
bioRxiv, 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, 2021
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
Federated Multi-Site Normative Modeling using Hierarchical Bayesian Regression
SM Kia, H Huijsdens, S Rutherford, R Dinga, T Wolfers, M Mennes, ...
bioRxiv, 2021
Non-linearity matters: a deep learning solution to generalization of hidden brain patterns across population cohorts
M Zabihi, SM Kia, T Wolfers, R Dinga, A Llera, D Bzdok, CF Beckmann, ...
bioRxiv, 2021
Systém momentálne nemôže vykonať operáciu. Skúste to neskôr.
Články 1–20