Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans. - Carlton Chu; Jeffrey De Fauw; Nenad Tomasev; Bernardino Romera-Paredes; Cían Hughes; Joseph R. Ledsam; Trevor Back; Hugh Montgomery; Geraint Rees 001; Rosalind Raine; Kevin Sullivan; Syed Ali Moinuddin; et al. (F1000Research, 2016)

Automated analysis of retinal imaging using machine learning techniques for computer vision. - Jeffrey De Fauw; Pearse A. Keane; Nenad Tomasev; Daniel Visentin; George van den Driessche 002; Mike Johnson; Cían Hughes; Carlton Chu; Joseph R. Ledsam; Trevor Back; Tunde Peto; Geraint Rees 001; et al. (F1000Research, 2016)

A Probabilistic U-Net for Segmentation of Ambiguous Images. - Simon Kohl; Bernardino Romera-Paredes; Clemens Meyer; Jeffrey De Fauw; Joseph R. Ledsam; Klaus H. Maier-Hein; S. M. Ali Eslami; Danilo Jimenez Rezende; Olaf Ronneberger (NeurIPS, 2018)

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy. - Stanislav Nikolov; Sam Blackwell; Ruheena Mendes; Jeffrey De Fauw; Clemens Meyer; Cían Hughes; Harry Askham; Bernardino Romera-Paredes; Alan Karthikesalingam; Carlton Chu; Dawn Carnell; Cheng Boon; et al. (CoRR, 2018)

Contrastive Training for Improved Out-of-Distribution Detection. - Jim Winkens; Rudy Bunel; Abhijit Guha Roy; Robert Stanforth; Vivek Natarajan; Joseph R. Ledsam; Patricia MacWilliams; Pushmeet Kohli; Alan Karthikesalingam; Simon Kohl; A. Taylan Cemgil; S. M. Ali Eslami; et al. (CoRR, 2020)

A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. - Sercan Ö. Arik; Joel Shor; Rajarishi Sinha; Jinsung Yoon; Joseph R. Ledsam; Long T. Le; Michael W. Dusenberry; Nathanael C. Yoder; Kris Popendorf; Arkady Epshteyn; Johan Euphrosine; Elli Kanal; et al. (npj Digit. Medicine, 2021)

AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions. - Hirofumi Tsuruta; Hiroyuki Yamazaki; Ryota Maeda; Ryotaro Tamura; Jennifer N. Wei; Zelda E. Mariet; Poomarin Phloyphisut; Hidetoshi Shimokawa; Joseph R. Ledsam; Lucy J. Colwell; Akihiro Imura (NeurIPS, 2023)

The unreasonable effectiveness of AI CADe polyp detectors to generalize to new countries. - Joel Shor; Hiro-o Yamano; Daisuke Tsurumaru; Yotam Intrator; Hiroki Kayama; Joseph R. Ledsam; Atsushi Hamabe; Koji Ando; Mitsuhiko Ota; Haruei Ogino; Hiroshi Nakase; Kaho Kobayashi; et al. (CoRR, 2023)

Predicting Generalization of AI Colonoscopy Models to Unseen Data. - Joel Shor; Carson McNeil; Yotam Intrator; Joseph R. Ledsam; Hiro-o Yamano; Daisuke Tsurumaru; Hiroki Kayama; Atsushi Hamabe; Koji Ando; Mitsuhiko Ota; Haruei Ogino; Hiroshi Nakase; et al. (CoRR, 2024)

Predicting the generalization of computer aided detection (CADe) models for colonoscopy. - Joel Shor; Carson McNeil; Yotam Intrator; Joseph R. Ledsam; Hiro-o Yamano; Daisuke Tsurumaru; Hiroki Kayama; Atsushi Hamabe; Koji Ando; Mitsuhiko Ota; Haruei Ogino; Hiroshi Nakase; et al. (Discov. Artif. Intell., 2024)