Search Results - "Adkinson, Brendan D."

Meta-Learning for Generalizable Connectome Modeling Across Heterogeneous Atlas Spaces

Liang, Qinghao, Adkinson, Brendan D., Scheinost, Dustin

2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)

Power and reproducibility in the external validation of brain-phenotype predictions

Rosenblatt, Matthew^{Aff1, IDs41562024019317_cor1}, Tejavibulya, Link, Sun, Huili, Camp, Chris C., Khaitova, Milana, Adkinson, Brendan D., Jiang, Rongtao, Westwater, Margaret L., Noble, Stephanie^{Aff3, Aff4, Aff5}, Scheinost, Dustin^{Aff1, Aff2, Aff3, Aff6, Aff7}

Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling

Liang, Qinghao^{Aff14, Aff18}, Adkinson, Brendan D.^{Aff15, Aff18}, Jiang, Rongtao^{Aff16, Aff18}, Scheinost, Dustin^{Aff14, Aff15, Aff16, Aff17, Aff18}

Goos, Gerhard, Series Editor^Aff1, Hartmanis, Juris, Founding Editor^Aff2, Bertino, Elisa, Editorial Board Member^Aff3, Gao, Wen, Editorial Board Member^Aff4, Steffen, Bernhard, Editorial Board Member^Aff5, Yung, Moti, Editorial Board Member^Aff6, Linguraru, Marius George, editor^Aff7, Dou, Qi, editor^Aff8, Feragen, Aasa, editor^Aff9, Giannarou, Stamatia, editor^Aff10, Glocker, Ben, editor^Aff11, Lekadir, Karim, editor^Aff12, Schnabel, Julia A., editor^Aff13

Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations

Adkinson, Brendan D., Rosenblatt, Matthew, Dadashkarimi, Javid, Tejavibulya, Link, Jiang, Rongtao, Noble, Stephanie, Scheinost, Dustin

White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis.

Di Biase, Maria A, Cetin-Karayumak, Suheyla, Lyall, Amanda E, Zalesky, Andrew, Cho, Kang Ik Kevin, Zhang, Fan, Kubicki, Marek, Rathi, Yogesh, Lyons, Monica G, Bouix, Sylvain, Billah, Tashrif, Anticevic, Alan, Schleifer, Charlie, Adkinson, Brendan D, Ji, Jie Lisa, Tamayo, Zailyn, Addington, Jean, Bearden, Carrie E, Cornblatt, Barbara A, Keshavan, Matcheri S, Mathalon, Daniel H, McGlashan, Thomas H, Perkins, Diana O, Cadenhead, Kristen S, Tsuang, Ming T, Woods, Scott W, Stone, William S, Shenton, Martha E, Cannon, Tyrone D, Pasternak, Ofer

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Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer

Scheinost, Dustin, Pollatou, Angeliki, Dufford, Alexander J., Jiang, Rongtao, Farruggia, Michael C., Rosenblatt, Matthew, Peterson, Hannah, Rodriguez, Raimundo X., Dadashkarimi, Javid, Liang, Qinghao, Dai, Wei, Foster, Maya L., Camp, Chris C., Tejavibulya, Link, Adkinson, Brendan D., Sun, Huili, Ye, Jean, Cheng, Qi, Spann, Marisa N., Rolison, Max, Noble, Stephanie, Westwater, Margaret L.

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Trends in self-citation rates in highimpact neurology, neuroscience, and psychiatry journals.

Rosenblatt, Matthew, Mehta, Saloni, Peterson, Hannah, Dadashkarimi, Javid, Rodriguez, Raimundo, Foster, Maya L., Adkinson, Brendan D., Liang, Qinghao, Kimble, Violet M., Ye, Jean, McCusker, Marie C., Farruggia, Michael C., Rolison, Max J., Westwater, Margaret L., Jiang, Rongtao, Noble, Stephanie, Scheinost, Dustin

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Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics

Demirtaş, Murat, Burt, Joshua B., Helmer, Markus, Ji, Jie Lisa, Adkinson, Brendan D., Glasser, Matthew F., Van Essen, David C., Sotiropoulos, Stamatios N., Anticevic, Alan, Murray, John D.

Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders

Foss-Feig, Jennifer H., Adkinson, Brendan D., Ji, Jie Lisa, Yang, Genevieve, Srihari, Vinod H., McPartland, James C., Krystal, John H., Murray, John D., Anticevic, Alan

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Broadening the Use of Machine Learning in Psychiatry

Adkinson, Brendan D., Chekroud, Adam M.

Mapping brain-behavior space relationships along the psychosis spectrum.

Jie Lisa Ji, Helmer, Markus, Fonteneau, Clara, Burt, Joshua B., Tamayo, Zailyn, Demšar, Jure, Adkinson, Brendan D., Savić, Aleksandar, Preller, Katrin H., Moujaes, Flora, Vollenweider, Franz X., Martin, William J., Repovš, Grega, Murray, John D., Anticevic, Alan

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Brain-phenotype predictions can survive across diverse real-world data.

Adkinson BD; Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, 06510, USA., Rosenblatt M; Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA., Dadashkarimi J; Department of Radiology, Athinoula. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.; Department of Radiology, Harvard Medical School, Boston, MA, 02129, USA., Tejavibulya L; Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, 06510, USA., Jiang R; Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA., Noble S; Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.; Department of Bioengineering, Northeastern University, Boston, MA, 02120, USA.; Department of Psychology, Northeastern University, Boston, MA, 02115, USA., Scheinost D; Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, 06510, USA.; Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.; Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.; Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA.; Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA.; Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA.

Preprint; Journal Article , 2024