Advanced machine learning in neuroimaging studies via federated learning

Federated analysis can help perform large-scale analyses using neuroimaging datasets across various research groups overcoming the limitations of institutional data-sharing policies, privacy or regulatory concerns as it requires no data sharing. In this work, we employ a federated neuromark algorithm to generate independent component analysis (ICA) time courses data from functional magnetic resonance imaging (fMRI) data and feed it to a federated deep neural network (DNN) model to perform classification of schizophrenia patients versus controls.

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Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825936
Primary Topic
Privacy-Preserving Technologies in Data
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article
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article

Advanced machine learning in neuroimaging studies via federated learning

Sunitha Basodi, Sandeep Panta, Vince D. Calhoun, Dylan Martin et al.
Privacy-Preserving Technologies in Data
article

Advanced machine learning in neuroimaging studies via federated learning

Sunitha Basodi, Sandeep Panta, Vince D. Calhoun, Dylan Martin, Javier Romero, Sergey Plis, Anand D. Sarwate
article en

Abstract

Federated analysis can help perform large-scale analyses using neuroimaging datasets across various research groups overcoming the limitations of institutional data-sharing policies, privacy or regulatory concerns as it requires no data sharing. In this work, we employ a federated neuromark algorithm to generate independent component analysis (ICA) time courses data from functional magnetic resonance imaging (fMRI) data and feed it to a federated deep neural network (DNN) model to perform classification of schizophrenia patients versus controls.

Rutgers, The State University of New Jersey (US), Georgia Institute of Technology (US), Emory University (US), Georgia State University (US), Center for Translational Research in Neuroimaging and Data Science (US)
Openalex Percentile: Top 77%
Privacy-Preserving Technologies in Data
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Advanced machine learning in neuroimaging studies via federated learning — Sunitha Basodi, Sandeep Panta, et al. · (2024) | TGRS Research Map | TGRS