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Showing 1–3 of 3 results

Advanced filters: Author: Jim Winkens Clear advanced filters

Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians

A collaboration system helps to integrate decisions between human experts and AI to optimize screening and triaging and to reduce clinicians’ workload.

Krishnamurthy (Dj) Dvijotham
Jim Winkens
Alan Karthikesalingam
Research17 Jul 2023
Nature Medicine

Volume: 29, P: 1814-1820
Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging

A representation-learning strategy for machine-learning models applied to medical-imaging tasks improves model robustness and training efficiency and mitigates suboptimal out-of-distribution performance.

Shekoofeh Azizi
Laura Culp
Vivek Natarajan
Research08 Jun 2023
Nature Biomedical Engineering

Volume: 7, P: 756-779
Predicting conversion to wet age-related macular degeneration using deep learning

In individuals diagnosed with age-related macular degeneration in one eye, a deep learning model can predict progression to the ‘wet’, sight-threatening form of the disease in the second eye within a 6-month time frame.

Jason Yim
Reena Chopra
Jeffrey De Fauw
Research18 May 2020
Nature Medicine

Volume: 26, P: 892-899