Age-Related Macular Degeneration (AMD), Diabetic Retinopathy (DR), and Glaucoma represent formidable challenges in the field of ophthalmology, collectively constituting leading retinal causes of vision impairment and blindness globally1. Early identification of pathological changes allows for the implementation of targeted interventions, ranging from lifestyle modifications and pharmacological treatments to surgical procedures. In ophthalmology, AI has emerged as a promising ally, offering the potential to revolutionize the diagnosis and management of ocular diseases, including AMD, DR, Glaucoma, ROP, and cataract2-4

  The Medios AI, developed by Medios Technologies, Remidio Innovative Solutions in Singapore, has designed algorithms to screen referable forms of DR, AMD, and Glaucoma. This AI system has undergone extensive validation upon integration with Remidio’s non-mydriatic smartphone-based fundus camera, known as Fundus on phone (FOP). Combining and developing a unified AI algorithm (Generic AI) capable of screening for various referable retinal conditions would offer significant advantages

  This prospective study will be conducted at the general outpatient department of AEH, Pondicherry. Every consecutive patient that consents to participate will sign a written informed consent form. Following a comprehensive eye examination, fundus imaging using the study device will be captured in all the participants and the generic AI algorithm will be run on the images captured. 

Methodology

All the participants will undergo a comprehensive eye examination as a part of routine eye care at the hospital. The medical record information including demographic details, best-corrected visual acuity, anterior and posterior segment examination details, goniosocopy (if Van-Herick grading 2 or less than grade 2), IOP, and other investigations (if any) conducted for final diagnosis of retinal conditions will be recorded.

The final diagnosis by the retina/glaucoma specialist along with the severity staging of the respective retinal or optic disc abnormality (if any) will be documented.

Patients evaluated in general clinic and noted to have a retinal pathology/glaucoma by examining doctor or flagged as referrable by AI will be referred to respective clinic. These patients will be evaluated by a consultant in the specialty clinic to ensure accuracy of clinical diagnosis. All the fundus images captured using reference standard fundus camera will be uploaded to a grading platform. Two specialists (one retina and one glaucoma) masked to clinical information and each other’s findings will grade (a) quality of images (disc and macula centered) captured, (b) grading of fundus images that are presented randomly.