| 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 | 152 | 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 | 120 | 2022 |
| Warped Bayesian linear regression for normative modelling of big data CJ Fraza, R Dinga, CF Beckmann, AF Marquand NeuroImage 245, 118715, 2021 | 78 | 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, 2021.06. 14.448106, 2021 | 38 | 2021 |
| Non-Gaussian normative modelling with hierarchical Bayesian regression AAA de Boer, JMM Bayer, SM Kia, S Rutherford, M Zabihi, C Fraza, ... Imaging Neuroscience 2, 1-36, 2024 | 16 | 2024 |
| Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data BR Bučková, C Fraza, R Rehák, M Kolenič, C Beckmann, F Španiel, ... eLife 13, 2025 | 9 | 2025 |
| PCNToolkit A Marquand, S Rutherford, SM Kia, T Wolfers, C Fraza, R Dinga, M Zabihi Zenodo https://doi. org/10.5281/zenodo 5207839, 2021 | 7 | 2021 |
| Normative modeling of neuroimaging data using generalized additive models of location scale and shape. bioRxiv, p. 2021.06. 14.448106 R Dinga, CJ Fraza, JMM Bayer, SM Kia, CF Beckmann, AF Marquand | 6 | 2021 |
| The Extremes of Normative Modelling C Fraza, M Zabihi, CF Beckmann, AF Marquand bioRxiv, 2022.08. 23.505049, 2022 | 5 | 2022 |
| Warped Bayesian linear regression for normative modelling of big data. NeuroImage, 245, Article 118715 CJ Fraza, R Dinga, CF Beckmann, AF Marquand | 5 | 2021 |
| Texture characterization by grey-level co-occurrence matrix from a perceptual approach A Gebejes, R Huertas, A Tremeau, I Tomic, PR Biswas, C Fraza, ... Color and Imaging Conference 24, 271-277, 2016 | 5 | 2016 |
| Personalising Alzheimer’s Disease progression using brain atrophy markers S Verdi, S Rutherford, C Fraza, D Tosun, A Altmann, LL Raket, JM Schott, ... medRxiv, 2023 | 4 | 2023 |
| To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling S Rutherford, T Wolfers, C Fraza, NG Harrnet, CF Beckmann, HG Ruhe, ... arXiv preprint arXiv:2407.19114, 2024 | 2 | 2024 |
| Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling S Verdi, S Rutherford, C Fraza, D Tosun, A Altmann, LL Raket, JM Schott, ... Alzheimer's & Dementia 20 (10), 6998-7012, 2024 | 1 | 2024 |
| Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps M Zabihi, SM Kia, T Wolfers, S de Boer, C Fraza, R Dinga, AL Arenas, ... Plos one 19 (8), e0308329, 2024 | 1 | 2024 |
| Explanatory latent representation of heterogeneous spatial maps of task-fmri in large-scale datasets M Zabihi, SM Kia, T Wolfers, S de Boer, C Fraza, S Soheili-Nezhad, ... bioRxiv, 2021.03. 10.434856, 2021 | 1 | 2021 |
| The underlying brain networks of superior memory C Fraza | 1 | 2020 |
| Unraveling the link between CNVs, cognition and individual neuroimaging deviation scores from a population-based reference cohort C Fraza, IE Sønderby, R Boen, Y Shi, CF Beckmann, AF Marquand Nature Mental Health, 1-13, 2024 | | 2024 |
| Learning latent profiles via cognitive growth charting in psychosis: design and rationale for the PRECOGNITION project AF Marquand, B Rehák Bučková, G Cattarinussi, C Flaaten, C Busch, ... medRxiv, 2024.11. 26.24317909, 2024 | | 2024 |
| Unraveling the Link between CNVs, General Cognition, and Individual Neuroimaging Deviation Scores from a Reference Cohort C Fraza, IE Sønderby, R Boen, Y Shi, CF Beckmann, AF Marquand medRxiv, 2023.11. 29.23298954, 2023 | | 2023 |