Stephanie Noble
Affiliations: | 2019 | Interdepartmental Neuroscience Program | Yale University, New Haven, CT |
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| Adkinson BD, Rosenblatt M, Dadashkarimi J, et al. (2024) Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations. Developmental Cognitive Neuroscience. 70: 101464 |
| Rosenblatt M, Tejavibulya L, Sun H, et al. (2024) Power and reproducibility in the external validation of brain-phenotype predictions. Nature Human Behaviour |
| Jiang R, Noble S, Rosenblatt M, et al. (2024) The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression. Nature Communications. 15: 4411 |
| Rodriguez RX, Noble S, Camp CC, et al. (2024) Connectome caricatures: removing large-amplitude co-activation patterns in resting-state fMRI emphasizes individual differences. Biorxiv : the Preprint Server For Biology |
| Rosenblatt M, Tejavibulya L, Jiang R, et al. (2024) Data leakage inflates prediction performance in connectome-based machine learning models. Nature Communications. 15: 1829 |
| Adkinson BD, Rosenblatt M, Dadashkarimi J, et al. (2024) Brain-phenotype predictions can survive across diverse real-world data. Biorxiv : the Preprint Server For Biology |
| Rosenblatt M, Tejavibulya L, Jiang R, et al. (2023) The effects of data leakage on connectome-based machine learning models. Biorxiv : the Preprint Server For Biology |
| Rosenblatt M, Tejavibulya L, Camp CC, et al. (2023) Power and reproducibility in the external validation of brain-phenotype predictions. Biorxiv : the Preprint Server For Biology |
| Camp CC, Noble S, Scheinost D, et al. (2023) Test-retest reliability of functional connectivity in depressed adolescents. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging |
| Sun H, Jiang R, Dai W, et al. (2023) Network controllability of structural connectomes in the neonatal brain. Nature Communications. 14: 5820 |