Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention. - Omneya Attallah; Alan Karthikesalingam; Peter J. E. Holt; Matthew M. Thompson; Rob Sayers; Matthew J. Bown; Eddie C. Choke; Xianghong Ma (BMC Medical Informatics Decis. Mak., 2017)

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)

Evaluation of a digitally-enabled care pathway for acute kidney injury management in hospital emergency admissions. - Alistair Connell; Hugh Montgomery; Peter Martin; Claire Nightingale; Omid Sadeghi-Alavijeh; Dominic King; Alan Karthikesalingam; Cían Hughes; Trevor Back; Kareem Ayoub; Mustafa Suleyman; Gareth Jones; et al. (npj Digit. Medicine, 2019)

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)

Concept-based model explanations for electronic health records. - Diana Mincu; Eric Loreaux; Shaobo Hou; Sebastien Baur; Ivan Protsyuk; Martin Seneviratne; Anne Mottram; Nenad Tomasev; Alan Karthikesalingam; Jessica Schrouff (CHIL, 2021)

Big Self-Supervised Models Advance Medical Image Classification. - Shekoofeh Azizi; Basil Mustafa; Fiona Ryan; Zachary Beaver; Jan Freyberg; Jonathan Deaton; Aaron Loh; Alan Karthikesalingam; Simon Kornblith; Ting Chen 007; Vivek Natarajan; Mohammad Norouzi 002 (ICCV, 2021)

Supervised Transfer Learning at Scale for Medical Imaging. - Basil Mustafa; Aaron Loh; Jan Freyberg; Patricia MacWilliams; Megan Wilson; Scott Mayer McKinney; Marcin Sieniek; Jim Winkens; Yuan Liu; Peggy Bui; Shruthi Prabhakara; Umesh Telang; et al. (CoRR, 2021)

Best of both worlds: local and global explanations with human-understandable concepts. - Jessica Schrouff; Sebastien Baur; Shaobo Hou; Diana Mincu; Eric Loreaux; Ralph Blanes; James Wexler; Alan Karthikesalingam; Been Kim (CoRR, 2021)

Multitask prediction of organ dysfunction in the intensive care unit using sequential subnetwork routing. - Subhrajit Roy; Diana Mincu; Eric Loreaux; Anne Mottram; Ivan Protsyuk; Natalie Harris; Yuan Xue; Jessica Schrouff; Hugh Montgomery; Alistair Connell; Nenad Tomasev; Alan Karthikesalingam; et al. (J. Am. Medical Informatics Assoc., 2021)

Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis. - Ravi Aggarwal; Viknesh Sounderajah; Guy Martin; Daniel S. W. Ting; Alan Karthikesalingam; Dominic King; Hutan Ashrafian; Ara Darzi (npj Digit. Medicine, 2021)

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. - Jessica Schrouff; Natalie Harris; Sanmi Koyejo; Ibrahim M. Alabdulmohsin; Eva Schnider; Krista Opsahl-Ong; Alexander Brown; Subhrajit Roy; Diana Mincu; Christina Chen; Awa Dieng; Yuan Liu; et al. (NeurIPS, 2022)

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? - Jessica Schrouff; Natalie Harris; Oluwasanmi Koyejo; Ibrahim Alabdulmohsin; Eva Schnider; Krista Opsahl-Ong; Alexander Brown; Subhrajit Roy; Diana Mincu; Christina Chen; Awa Dieng; Yuan Liu; et al. (CoRR, 2022)

Robust and Efficient Medical Imaging with Self-Supervision. - Shekoofeh Azizi; Laura Culp; Jan Freyberg; Basil Mustafa; Sebastien Baur; Simon Kornblith; Ting Chen 007; Patricia MacWilliams; S. Sara Mahdavi; Ellery Wulczyn; Boris Babenko; Megan Wilson; et al. (CoRR, 2022)

Metrics reloaded: Pitfalls and recommendations for image analysis validation. - Lena Maier-Hein; Annika Reinke; Evangelia Christodoulou; Ben Glocker; Patrick Godau; Fabian Isensee; Jens Kleesiek; Michal Kozubek 001; Mauricio Reyes 001; Michael A. Riegler; Manuel Wiesenfarth; Michael Baumgartner 001; et al. (CoRR, 2022)

Detecting and Preventing Shortcut Learning for Fair Medical AI using Shortcut Testing (ShorT). - Alexander Brown; Nenad Tomasev; Jan Freyberg; Yuan Liu; Alan Karthikesalingam; Jessica Schrouff (CoRR, 2022)

Large Language Models Encode Clinical Knowledge. - Karan Singhal; Shekoofeh Azizi; Tao Tu 001; S. Sara Mahdavi; Jason Wei; Hyung Won Chung; Nathan Scales; Ajay Kumar Tanwani; Heather Cole-Lewis; Stephen Pfohl; Perry Payne; Martin Seneviratne; et al. (CoRR, 2022)

Underspecification Presents Challenges for Credibility in Modern Machine Learning. - Alexander D'Amour; Katherine A. Heller; Dan Moldovan; Ben Adlam; Babak Alipanahi; Alex Beutel; Christina Chen; Jonathan Deaton; Jacob Eisenstein; Matthew D. Hoffman; Farhad Hormozdiari; Neil Houlsby; et al. (J. Mach. Learn. Res., 2022)

Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions. - Abhijit Guha Roy; Jie Ren 006; Shekoofeh Azizi; Aaron Loh; Vivek Natarajan; Basil Mustafa; Nick Pawlowski; Jan Freyberg; Yuan Liu; Zachary Beaver; Nam Vo; Peggy Bui; et al. (Medical Image Anal., 2022)

Understanding metric-related pitfalls in image analysis validation. - Annika Reinke; Minu Tizabi; Michael Baumgartner 001; Matthias Eisenmann; Doreen Heckmann-Nötzel; A. Emre Kavur; Tim Rädsch; Carole H. Sudre; Laura Ación; Michela Antonelli; Tal Arbel; Spyridon Bakas; et al. (CoRR, 2023)

Generative models improve fairness of medical classifiers under distribution shifts. - Ira Ktena; Olivia Wiles; Isabela Albuquerque; Sylvestre-Alvise Rebuffi; Ryutaro Tanno; Abhijit Guha Roy; Shekoofeh Azizi; Danielle Belgrave; Pushmeet Kohli; Alan Karthikesalingam; A. Taylan Cemgil; Sven Gowal (CoRR, 2023)

Towards Expert-Level Medical Question Answering with Large Language Models. - Karan Singhal; Tao Tu 001; Juraj Gottweis; Rory Sayres; Ellery Wulczyn; Le Hou; Kevin Clark; Stephen Pfohl; Heather Cole-Lewis; Darlene Neal; Mike Schaekermann; Amy Wang; et al. (CoRR, 2023)

Evaluating AI systems under uncertain ground truth: a case study in dermatology. - David Stutz; Ali Taylan Cemgil; Abhijit Guha Roy; Tatiana Matejovicova; Melih Barsbey; Patricia Strachan; Mike Schaekermann; Jan Freyberg; Rajeev V. Rikhye; Beverly Freeman; Javier Perez Matos; Umesh Telang; et al. (CoRR, 2023)

Towards Generalist Biomedical AI. - Tao Tu 001; Shekoofeh Azizi; Danny Driess; Mike Schaekermann; Mohamed Amin; Pi-Chuan Chang; Andrew Carroll; Chuck Lau; Ryutaro Tanno; Ira Ktena; Basil Mustafa; Aakanksha Chowdhery; et al. (CoRR, 2023)

The Capability of Large Language Models to Measure Psychiatric Functioning. - Isaac R. Galatzer-Levy; Daniel McDuff; Vivek Natarajan; Alan Karthikesalingam; Matteo Malgaroli (CoRR, 2023)

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation. - Ryutaro Tanno; David G. T. Barrett; Andrew Sellergren; Sumedh Ghaisas; Sumanth Dathathri; Abigail See; Johannes Welbl; Karan Singhal; Shekoofeh Azizi; Tao Tu 001; Mike Schaekermann; Rhys May; et al. (CoRR, 2023)

Towards Accurate Differential Diagnosis with Large Language Models. - Daniel McDuff; Mike Schaekermann; Tao Tu 001; Anil Palepu; Amy Wang; Jake Garrison; Karan Singhal; Yash Sharma; Shekoofeh Azizi; Kavita Kulkarni; Le Hou; Yong Cheng; et al. (CoRR, 2023)

Conversational AI in health: Design considerations from a Wizard-of-Oz dermatology case study with users, clinicians and a medical LLM. - Brenna Li; Amy Wang; Patricia Strachan; Julie Anne Séguin; Sami Lachgar; Karyn C. Schroeder; Mathias S. Fleck; Renee Wong; Alan Karthikesalingam; Vivek Natarajan; Yossi Matias; Gregory S. Corrado; et al. (CHI Extended Abstracts, 2024)

Towards Conversational Diagnostic AI. - Tao Tu 001; Anil Palepu; Mike Schaekermann; Khaled Saab 003; Jan Freyberg; Ryutaro Tanno; Amy Wang; Brenna Li; Mohamed Amin; Nenad Tomasev; Shekoofeh Azizi; Karan Singhal; et al. (CoRR, 2024)

MINT: A wrapper to make multi-modal and multi-image AI models interactive. - Jan Freyberg; Abhijit Guha Roy; Terry Spitz; Beverly Freeman; Mike Schaekermann; Patricia Strachan; Eva Schnider; Renee Wong; Dale R. Webster; Alan Karthikesalingam; Yun Liu 013; Krishnamurthy Dvijotham; et al. (CoRR, 2024)

Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset. - Abbi Ward; Jimmy Li; Julie Wang; Sriram Lakshminarasimhan; Ashley Carrick; Bilson J. L. Campana; Jay Hartford; Pradeep Kumar S; Tiya Tiyasirichokchai; Sunny Virmani; Renee Wong; Yossi Matias; et al. (CoRR, 2024)

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. - Stephen R. Pfohl; Heather Cole-Lewis; Rory Sayres; Darlene Neal; Mercy Nyamewaa Asiedu; Awa Dieng; Nenad Tomasev; Qazi Mamunur Rashid; Shekoofeh Azizi; Negar Rostamzadeh; Liam G. McCoy; Leo Anthony Celi; et al. (CoRR, 2024)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)

Towards Democratization of Subspeciality Medical Expertise. - Jack W. O'Sullivan; Anil Palepu; Khaled Saab 003; Wei-Hung Weng; Yong Cheng; Emily Chu; Yaanik Desai; Aly Elezaby; Daniel Seung Kim; Roy Lan; Wilson Tang; Natalie Tapaskar; et al. (CoRR, 2024)

Exploring Large Language Models for Specialist-level Oncology Care. - Anil Palepu; Vikram Dhillon; Polly Niravath; Wei-Hung Weng; Preethi Prasad; Khaled Saab 003; Ryutaro Tanno; Yong Cheng; Hanh Mai; Ethan Burns; Zainub Ajmal; Kavita Kulkarni; et al. (CoRR, 2024)

Generative AI for medical education: Insights from a case study with medical students and an AI tutor for clinical reasoning. - Amy Wang; Roma Ruparel; Anna Iurchenko; Paul Jhun; Julie Anne Séguin; Patricia Strachan; Renee Wong; Alan Karthikesalingam; Yossi Matias; Avinatan Hassidim; Dale R. Webster; Christopher Semturs; et al. (CHI Extended Abstracts, 2025)

Evaluating medical AI systems in dermatology under uncertain ground truth. - David Stutz; Ali Taylan Cemgil; Abhijit Guha Roy; Tatiana Matejovicova; Melih Barsbey; Patricia Strachan; Mike Schaekermann; Jan Freyberg; Rajeev Rikhye; Beverly Freeman; Javier Perez Matos; Umesh Telang; et al. (Medical Image Anal., 2025)

Towards an AI co-scientist. - Juraj Gottweis; Wei-Hung Weng; Alexander N. Daryin; Tao Tu 001; Anil Palepu; Petar Sirkovic; Artiom Myaskovsky; Felix Weissenberger; Keran Rong; Ryutaro Tanno; Khaled Saab 003; Dan Popovici; et al. (CoRR, 2025)

Towards Conversational AI for Disease Management. - Anil Palepu; Valentin Liévin; Wei-Hung Weng; Khaled Saab 003; David Stutz; Yong Cheng; Kavita Kulkarni; S. Sara Mahdavi; Joelle K. Barral; Dale R. Webster; Katherine Chou; Avinatan Hassidim; et al. (CoRR, 2025)

Advancing Conversational Diagnostic AI with Multimodal Reasoning. - Khaled Saab 003; Jan Freyberg; Chunjong Park; Tim Strother; Yong Cheng; Wei-Hung Weng; David G. T. Barrett; David Stutz; Nenad Tomasev; Anil Palepu; Valentin Liévin; Yash Sharma; et al. (CoRR, 2025)

Towards physician-centered oversight of conversational diagnostic AI. - Elahe Vedadi; David G. T. Barrett; Natalie Harris; Ellery Wulczyn; Shashir Reddy; Roma Ruparel; Mike Schaekermann; Tim Strother; Ryutaro Tanno; Yash Sharma; Jihyeon Lee; Cían Hughes; et al. (CoRR, 2025)