Joseph R. Ledsam

According to our database, Joseph R. Ledsam authored at least 9 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

CoRR, 2024

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, Eiji Oki, Roman Goldenberg, Ehud Rivlin, Ichiro Takemasa

CoRR, 2023

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

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, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister

npj Digit. Medicine, 2021

2020

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, Olaf Ronneberger

CoRR, 2020

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, Derek D'Souza, Syed Ali Moinuddin, Kevin Sullivan, DeepMind Radiographer Consortium, Hugh Montgomery, Geraint Rees, Ricky Sharma, Mustafa Suleyman, Trevor Back, Joseph R. Ledsam, Olaf Ronneberger

CoRR, 2018

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

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

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, Mike Johnson, Cían Hughes, Carlton Chu, Joseph R. Ledsam, Trevor Back, Tunde Peto, Geraint Rees, Hugh Montgomery, Rosalind Raine, Olaf Ronneberger, Julien Cornebise

F1000Research, 2016

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, Rosalind Raine, Kevin Sullivan, Syed Ali Moinuddin, Derek D'Souza, Olaf Ronneberger, Ruheena Mendes, Julien Cornebise

F1000Research, 2016