Pearse A. Keane
Orcid: 0000-0002-9239-745X
According to our database1,
Pearse A. Keane authored at least 35 papers
between 2016 and 2026.
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Bibliography
2026
Vibe coding for clinicians: democratising bespoke software development for digital health innovation.
CoRR, April, 2026
Deliberative multi-agent large language models improve clinical reasoning in ophthalmology.
CoRR, March, 2026
Considering the missing science of retraining and maintenance in medical artificial intelligence, using ophthalmology as an exemplar.
npj Digit. Medicine, 2026
Flight rules for clinical AI: lessons from aviation for human-AI collaboration in medicine.
npj Digit. Medicine, 2026
Current challenges and the way forwards for regulatory databases of artificial intelligence as a medical device.
npj Digit. Medicine, 2026
Matters Arising: Near-identical images, not foundation models, explain purported re-identification of patients from medical imaging.
npj Digit. Medicine, 2026
Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026
2025
Native Intelligence Emerges from Large-Scale Clinical Practice: A Retinal Foundation Model with Deployment Efficiency.
CoRR, December, 2025
Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics.
CoRR, September, 2025
FusionFM: Fusing Eye-specific Foundational Models for Optimized Ophthalmic Diagnosis.
CoRR, August, 2025
CoRR, August, 2025
Is an Ultra Large Natural Image-Based Foundation Model Superior to a Retina-Specific Model for Detecting Ocular and Systemic Diseases?
CoRR, February, 2025
Are Traditional Deep Learning Model Approaches as Effective as a Retinal-Specific Foundation Model for Ocular and Systemic Disease Detection?
CoRR, January, 2025
CoRR, January, 2025
A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America.
npj Digit. Medicine, 2025
npj Digit. Medicine, 2025
Efficient Foundation Model Pre-training on Mixed Retina Images from Similar Modalities.
Proceedings of the Efficient Medical Artificial Intelligence, 2025
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025
2024
CF-Loss: Clinically-relevant feature optimised loss function for retinal multi-class vessel segmentation and vascular feature measurement.
Medical Image Anal., 2024
Block Expanded DINORET: Adapting Natural Domain Foundation Models for Retinal Imaging Without Catastrophic Forgetting.
CoRR, 2024
Common and Rare Fundus Diseases Identification Using Vision-Language Foundation Model with Knowledge of Over 400 Diseases.
CoRR, 2024
2022
VAFO-Loss: VAscular Feature Optimised Loss Function for Retinal Artery/Vein Segmentation.
CoRR, 2022
2021
Nat. Mach. Intell., 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
"Yes, but will it work for my patients?" Driving clinically relevant research with benchmark datasets.
npj Digit. Medicine, 2020
Proceedings of the 8th International Conference on 3D Vision, 2020
2019
A Hybrid Machine Learning Approach Using LBP Descriptor and PCA for Age-Related Macular Degeneration Classification in OCTA Images.
Proceedings of the Medical Image Understanding and Analysis - 23rd Conference, 2019
Proceedings of the 21st International Conference on Transparent Optical Networks, 2019
2018
Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.
CoRR, 2018
2017
Proceedings of the IEEE International Conference on Computer Vision, 2017
2016
Automated analysis of retinal imaging using machine learning techniques for computer vision.
F1000Research, 2016