Noah Hillman

The paper introduces MIRTH, an imputation-based harmonization method that mitigates site effects in neuroimaging data without data leakage, achieving high predictive accuracy in machine learning studies.

The paper presents a curated dataset of processed diffusion MRI data from the ABCD Study, showing that specific diffusion metrics are sensitive to adolescent white matter development and robust to image quality variation.