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Biophysics-informed deep operator learning for inverse problems with application to electrophysiological source reconstruction
Eardi Lila, Erica R. Peterson, Alexis N. Bosseler +2
Electrophysiological brain signals are typically acquired through indirect and noisy measurements, providing transformed representations of the underlying neural activity. Source r…
Learned Hemodynamic Coupling Inference in Resting-State Functional MRI
William Consagra, Eardi Lila
Functional magnetic resonance imaging (fMRI) provides an indirect measurement of neuronal activity via hemodynamic responses that vary across brain regions and individuals. Ignorin…
Dimension-reduced outcome-weighted learning for estimating individualized treatment regimes in observational studies
Sungtaek Son, Eardi Lila, Kwun Chuen Gary Chan
Individualized treatment regimes (ITRs) aim to improve clinical outcomes by assigning treatment based on patient-specific characteristics. However, existing methods often struggle…