Enhancing Cancer Prediction in Challenging Screen-Detected Incident Lung Nodules Using Time-Series Deep Learning. - Shahab Aslani; Pavan Alluri; Eyjolfur Gudmundsson; Edward Chandy; John McCabe; Anand Devaraj; Carolyn Horst; Sam M. Janes; Rahul Chakkara; Arjun Nair; Daniel C. Alexander; SUMMIT Consortium; et al. (CoRR, 2022)

A data-centric deep learning approach to airway segmentation. - Wing Keung Cheung; Ashkan Pakzad; Nesrin Mogulkoc; Sarah Needleman; Bojidar Rangelov; Eyjolfur Gudmundsson; An Zhao; Mariam Abbas; Davina McLaverty; Dimitrios Asimakopoulos; Robert Chapman; Recep Savas; et al. (CoRR, 2023)

Exploring Fairness in State-of-the-Art Pulmonary Nodule Detection Algorithms. - John McCabe; Daryl Cheng; Amyn Bhamani; Monica Mullin; Tanya Patrick; Arjun Nair; Sam M. Janes; Carole H. Sudre; Joseph Jacob (FAIMI/EPIMI@MICCAI, 2024)

Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning. - Shahab Aslani; Pavan Alluri; Eyjolfur Gudmundsson; Edward Chandy; John McCabe; Anand Devaraj; Carolyn Horst; Sam M. Janes; Rahul Chakkara; Daniel C. Alexander; Arjun Nair; Joseph Jacob (Comput. Medical Imaging Graph., 2024)

Interpolation-split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance. - Wing Keung Cheung; Ashkan Pakzad; Nesrin Mogulkoc; Sarah Needleman; Bojidar Rangelov; Eyjolfur Gudmundsson; An Zhao; Mariam Abbas; Davina McLaverty; Dimitrios Asimakopoulos; Robert Chapman; Recep Savas; et al. (J. Big Data, 2024)

A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs. - Niccolò McConnell; Pardeep Vasudev; Daisuke Yamada; Daryl Cheng; Mehran Azimbagirad; John McCabe; Shahab Aslani; Ahmed H. Shahin; Yukun Zhou; SUMMIT Consortium; André Altmann; Yipeng Hu; et al. (CoRR, 2025)