AI-MK: artificial intelligence for assessing and monitoring microbial keratitis
This AI framework reliably identified MK lesions using AS-OCT, with high sensitivity and specificity. The framework was able to identify change in most cases compared with corneal specialists.
Authors
- Alfredo Borgia (ORCID: https://orcid.org/0000-0002-3976-242X)
- Colby Hart (ORCID: https://orcid.org/0000-0002-3739-8177)
- Matteo Airaldi (ORCID: https://orcid.org/0000-0001-9010-1208)
- Gibran Butt (ORCID: https://orcid.org/0000-0001-5306-4647)
- Giulia Coco (ORCID: https://orcid.org/0009-0007-5459-566X)
- Stephen B. Kaye (ORCID: https://orcid.org/0000-0003-0390-0592)
- Yalin Zheng (ORCID: https://orcid.org/0000-0002-7873-0922)
- Adela Hulpus
- Chen Xu (ORCID: https://orcid.org/0009-0005-0957-8751)
- Tobi Somerville
- Vito Romano
- Mahmoud Ahmed
- Daniel Mahini
Institutions
- Università Cattolica del Sacro Cuore (IT)
- University of Liverpool (GB)
- Queen Mary University of London (GB)
- University of Cambridge (GB)
- Royal Liverpool University Hospital (GB)
- Luigi Sacco Hospital (IT)
- The Royal Victorian Eye & Ear Hospital (AU)
- Birmingham and Midland Eye Centre (GB)
- Universidad Humanitas (MX)
- University of Birmingham (GB)
- University of Brescia (IT)
Publication Details
- Journal
- BMJ Open Ophthalmology
- Published
- 2026-01-13
- DOI
- https://doi.org/10.1136/bmjophth-2025-002556
- Primary Topic
- Ocular Infections and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- UK Research and Innovation
- National Institute for Health and Care Research
- Department of Health and Social Care
- Medical Research Council
- Birmingham Biomedical Research Centre