{
  "abstract": "Background/Aims To evaluate the performance of an artificial intelligence (AI) model for detecting and monitoring microbial keratitis (MK) using anterior segment optical coherence tomography (AS-OCT).Methods This is a prospective observational study. Patients with clinically suspected MK and healthy participants were included. In addition to routine assessment and treatment with topical fluoroquinolone therapy, patients underwent AS-OCT at each clinic visit. These images were tested on our DeepLabV3 network-based AI model, which aims to diagnose and record changes to infiltrate sizes of MK lesions over time.Results The AI model accurately captured MK lesions in 93% of cases (152/163). MK was not detected in scans from healthy eyes, and there were no cases of artefact being falsely detected. The model had a sensitivity of 93% (95% CI 88% to 97%), specificity of 100% (95% CI 88% to 100%), positive predictive value of 100% (95% CI 98% to 100%) and negative predictive value of 73% (95% CI 61% to 83%). Using only the corneal component with masking of the anterior chamber, the AI model showed agreement on change with both observers in 76% (13/18) cases.Conclusions 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": [
    {
      "affiliations": [
        "Cornea, The Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia"
      ],
      "name": "Colby Hart"
    },
    {
      "affiliations": [
        "Heart and Lung Research Institute, University of Cambridge, Cambridge, UK",
        "Digital Environment Research Institute, Queen Mary University of London, London, UK"
      ],
      "name": "Xu Chen"
    },
    {
      "affiliations": [
        "Department of Eye and Vision Science, University of Liverpool, Liverpool, UK"
      ],
      "name": "Mahmoud Ahmed"
    },
    {
      "affiliations": [
        "Department of Biomedical and Clinical Science “Luigi Sacco”, University of Milan, Milano, Italy"
      ],
      "name": "Matteo Airaldi"
    },
    {
      "affiliations": [
        "Department of Corneal and External Eye Diseases, Royal Liverpool University Hospital, Liverpool, UK",
        "Department of Biomedical Sciences, Humanitas University, Mexico City, Mexico"
      ],
      "name": "Alfredo Borgia"
    },
    {
      "affiliations": [
        "The Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia"
      ],
      "name": "Daniel Mahini"
    },
    {
      "affiliations": [
        "Department of Eye and Vision Sciences, University of Liverpool, Institute of Ageing and Chronic Disease, Liverpool, UK"
      ],
      "name": "Tobi Somerville"
    },
    {
      "affiliations": [
        "Academic Unit of Ophthalmology, University of Birmingham, Birmingham, UK",
        "SWBH NHS Trust, Birmingham and Midland Eye Centre, Birmingham, UK"
      ],
      "name": "Saaeha Rauz"
    },
    {
      "affiliations": [
        "Department of Eye and Vision Science, University of Liverpool, Liverpool, UK",
        "Royal Liverpool University Hospital, Liverpool, UK"
      ],
      "name": "Adela Hulpus"
    },
    {
      "affiliations": [
        "University of Brescia, Brescia, Italy"
      ],
      "name": "Vito Romano"
    },
    {
      "affiliations": [
        "Academic Unit of Ophthalmology, University of Birmingham College of Medical and Dental Sciences, Birmingham, UK"
      ],
      "name": "Gibran Butt"
    },
    {
      "affiliations": [
        "Ophthalmology, Catholic University, Rome, Italy"
      ],
      "name": "Giulia Coco"
    },
    {
      "affiliations": [
        "Department of Eye and Vision Science, University of Liverpool, Liverpool, UK",
        "Royal Liverpool University Hospital, Liverpool, UK"
      ],
      "name": "Yalin Zheng"
    },
    {
      "affiliations": [
        "Department of Eye and Vision Science, University of Liverpool, Liverpool, UK",
        "Royal Liverpool University Hospital, Liverpool, UK"
      ],
      "name": "Stephen Kaye"
    }
  ],
  "title": "AI-MK: artificial intelligence for assessing and monitoring microbial keratitis",
  "uid": "4a7a2796-6bde-5b80-85e3-35d7919735ac"
}