Machine learning and glioma imaging biomarkers. - Thomas C. Booth; Matthew Williams; Aysha Luis; Manuel Jorge Cardoso; Ashkan Keyoumars; Haris Shuaib (CoRR, 2019)

Machine Learning and Glioblastoma: Treatment Response Monitoring Biomarkers in 2021. - Thomas C. Booth; Bernice Akpinar; Andrei Roman; Haris Shuaib; Aysha Luis; Alysha Chelliah; Ayisha Al Busaidi; Ayesha Mirchandani; Burcu Alparslan; Nina Mansoor; Keyoumars Ashkan; Sébastien Ourselin; et al. (MLCN/RNO-AI@MICCAI, 2020)

MONAI: An open-source framework for deep learning in healthcare. - M. Jorge Cardoso; Wenqi Li 001; Richard Brown 004; Nic Ma; Eric Kerfoot; Yiheng Wang; Benjamin Murray; Andriy Myronenko; Can Zhao 001; Dong Yang 005; Vishwesh Nath; Yufan He; et al. (CoRR, 2022)

Current State of Community-Driven Radiological AI Deployment in Medical Imaging. - Vikash Gupta; Barbaros Selnur Erdal; Carolina Ramirez; Ralf Floca; Laurence Jackson; Brad W. Genereaux; Sidney Bryson; Christopher P. Bridge; Jens Kleesiek; Felix Nensa; Rickmer Braren; Khaled Younis; et al. (CoRR, 2022)

Moving towards vertically integrated artificial intelligence development. - Joe Zhang; Sanjay Budhdeo; William Wasswa; Paul Cerrato; Haris Shuaib; Harpreet Sood; Hutan Ashrafian; John D. Halamka; James T. Teo (npj Digit. Medicine, 2022)

Validating Transformers for Redaction of Text from Electronic Health Records in Real-World Healthcare. - Zeljko Kraljevic; Anthony Shek; Joshua Au Yeung; Ewart Jonathan Sheldon; Haris Shuaib; Mohammad Al-Agil; Xi Bai; Kawsar Noor; Anoop D. Shah; Richard J. B. Dobson; James T. Teo (ICHI, 2023)

Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium. - Haris Shuaib; Gareth J. Barker; Peter Sasieni; Enrico De Vita; Alysha Chelliah; Roman Andrei; Keyoumars Ashkan; Erica Beaumont; Lucy Brazil; Chris Rowland-Hill; Yue Hui Lau; Aysha Luis; et al. (CoRR, 2024)