{
  "abstract": "Purpose To investigate the diagnostic accuracy, feasibility and end-user experiences of an artificial intelligence (AI)-based, automated diabetic retinopathy (DR) screening model in real-world, Australian primary care and endocrinology clinics.Methods In a pragmatic trial conducted across five sites including general practice and endocrinology clinics, from August 2021 to June 2023, patients aged ≥50 years, and those aged ≥18 years with diabetes were screened using an AI-integrated, non-mydriatic fundus camera. The AI instantly analysed the retinal images for referable DR. Patients detected with referable DR or ungradable images were referred to eyecare professionals. The accuracy of the AI grading was assessed against gold standard human grading. A satisfaction survey was administered among the participants and care providers.Results Among 863 participants enrolled (mean (SD) age: 62.6 (13.2) years; 53.0% women), the AI system achieved high accuracy of 93.3% (95% CI: 91.4% to 95.5%) for referable DR detection, with a sensitivity of 83.7% (95% CI: 78.2% to 88.3%), specificity of 96.1% (95% CI: 94.7% to 97.2%) and an area under the receiver operating characteristic curve of 0.899 (95% CI: 0.874 to 0.924). The proportion of ungradable images was lower according to the AI grading (13.4%) compared with human grading (15.6%). Most patients (86%) and care providers (85%) expressed high satisfaction with the AI system.Conclusions The AI-assisted DR screening model was accurate and well received by patients and staff in Australian primary care and endocrinology clinics. This opportunistic screening model holds promise for enhancing early DR detection in non-eyecare settings, potentially preventing vision loss due to DR on a considerable scale.",
  "authors": [
    {
      "affiliations": [
        "Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia",
        "Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Victoria, Australia",
        "Lions Aravind Institute of Community Ophthalmology, Aravind Eye Care System, Madurai, Tamil Nadu, India"
      ],
      "name": "Sanil Joseph"
    },
    {
      "affiliations": [
        "School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR"
      ],
      "name": "Yueye Wang"
    },
    {
      "affiliations": [
        "Centre for Ophthalmology and Visual Science, The University of Western Australia, Nedlands, Western Australia, Australia",
        "Lions Outback Vision, Lions Eye Institute, Nedlands, Western Australia, Australia"
      ],
      "name": "Jocelyn J Drinkwater"
    },
    {
      "affiliations": [
        "Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia",
        "Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Victoria, Australia"
      ],
      "name": "Catherine Lingxue Jan"
    },
    {
      "affiliations": [
        "Lions Aravind Institute of Community Ophthalmology, Aravind Eye Care System, Madurai, Tamil Nadu, India"
      ],
      "name": "Balagiri Sundar"
    },
    {
      "affiliations": [
        "Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia",
        "Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Victoria, Australia"
      ],
      "name": "Zhuoting Zhu"
    },
    {
      "affiliations": [
        "School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR"
      ],
      "name": "Xianwen Shang"
    },
    {
      "affiliations": [
        "Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia"
      ],
      "name": "Jacqueline Henwood"
    },
    {
      "affiliations": [
        "Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Victoria, Australia"
      ],
      "name": "Katerina Kiburg"
    },
    {
      "affiliations": [
        "Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Victoria, Australia"
      ],
      "name": "Malcolm Clark"
    },
    {
      "affiliations": [
        "Department of Endocrinology & Diabetes, St Vincent's Hosptial Melbourne, Fitzroy, Victoria, Australia",
        "Department of Medicine, Univeristy of Melbourne, Fitzroy, Victoria, Melbourne",
        "Australian Centre for Accelerating Diabetes Innovations, Univeristy of Melbourne, Parkville, Victoria, Australia"
      ],
      "name": "Richard J MacIsaac"
    },
    {
      "affiliations": [
        "Centre for Ophthalmology and Visual Science, The University of Western Australia, Nedlands, Western Australia, Australia",
        "Lions Outback Vision, Lions Eye Institute, Nedlands, Western Australia, Australia"
      ],
      "name": "Angus W Turner"
    },
    {
      "affiliations": [
        "Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia",
        "Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Victoria, Australia",
        "The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia"
      ],
      "name": "Peter Van Wijngaarden"
    },
    {
      "affiliations": [
        "Lions Aravind Institute of Community Ophthalmology, Aravind Eye Care System, Madurai, Tamil Nadu, India"
      ],
      "name": "Thulasiraj D Ravilla"
    },
    {
      "affiliations": [
        "Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia",
        "School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR",
        "Research Centre for SHARP Vision (RCSV), The Hong Kong Polytechnic University, Kowloon, Hong Kong",
        "Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong"
      ],
      "name": "Ming Guang He"
    }
  ],
  "title": "Effectiveness of artificial intelligence-based diabetic retinopathy screening in primary care and endocrinology settings in Australia: a pragmatic trial",
  "uid": "ce9e49be-c439-578f-a1b2-8cb18277eca2"
}