A Machine Learning Approach to Predict Acute Ischemic Stroke Thrombectomy Reperfusion using Discriminative MR Image Features. - Haoyue Zhang; Jennifer Polson; Kambiz Nael; Noriko Salamon; Bryan Yoo; William Speier; Corey W. Arnold (BHI, 2021)

A Semi-Supervised Learning Framework to Leverage Proxy Information for Stroke MRI Analysis. - Jennifer Polson; Haoyue Zhang; Kambiz Nael; Noriko Salamon; Bryan Yoo; Namkug Kim; Dong-Wha Kang; William Speier; Corey W. Arnold (EMBC, 2021)

Intra-domain task-adaptive transfer learning to determine acute ischemic stroke onset time. - Haoyue Zhang; Jennifer S. Polson; Kambiz Nael; Noriko Salamon; Bryan Yoo; Suzie El-Saden; Fabien Scalzo; William Speier; Corey W. Arnold (Comput. Medical Imaging Graph., 2021)

Eigenrank by committee: Von-Neumann entropy based data subset selection and failure prediction for deep learning based medical image segmentation. - Bilwaj Gaonkar; Joel Beckett; Mark Attiah; Christine S. Ahn; Matthew Edwards; Bayard Wilson; Azim Laiwalla; Banafsheh Salehi; Bryan Yoo; Alex A. T. Bui; Luke Macyszyn (Medical Image Anal., 2021)

Ensembling mitigates scanner effects in deep learning medical image segmentation with deep-U-Nets. - Anshul Ratnaparkhi; Bilwaj Gaonkar; David Zarrin; Ien Li; Kirstin Cook; Azim Laiwalla; Bayard Wilson; Mark Attiah; Christine S. Ahn; Diane Villaroman; Bryan Yoo; Banafsheh Salehi; et al. (Computer-Aided Diagnosis, 2022)