Recently, the Armed Forces Medical Services (AFMS) launched India’s first Artificial Intelligence–driven community screening programme for Diabetic Retinopathy, in collaboration with All India Institute of Medical Sciences (AIIMS), New Delhi and the Ministry of Health & Family Welfare (MoHFW).

About AI-Driven Community Screening for Diabetic Retinopathy

• Pioneering Technology: The program utilizes MadhuNetrAI, a web-based AI tool developed by AIIMS, to perform automated screening, grading, and triaging of retinal images captured via handheld fundus cameras.
• Aim: To ensure early detection and referral of Diabetic Retinopathy, create real-time national disease intelligence, and prevent avoidable blindness through scalable community screening.
• Key Features:
  • AI-enabled screening using handheld fundus cameras
  • Task-shifting: Screening by trained Medical Officers, nurses, and health assistants
  • Real-time health intelligence on disease prevalence and geographic distribution
  • Referral linkage to District Hospitals and vitreo-retina specialists
  • Pilot rollout across urban, rural, coastal, hilly, and remote regions
• Significance:
  • Enables early detection and timely referral, reducing avoidable blindness
  • Strengthens primary and community healthcare systems
  • Demonstrates ethical and assistive use of Artificial Intelligence in public health
  • Creates a scalable national model for Non-Communicable Disease (NCD) screening
  • With over 65 million diabetics in India and nearly 90% lacking access to retinal exams, the AI bridges the specialist shortage by enabling “doorstep” diagnostic services.

About Diabetic Retinopathy (DR)

• Refers: Diabetic Retinopathy (DR) is a diabetes-related retinal disease caused by damage to the small blood vessels of the retina, the light-sensitive layer at the back of the eye. 
  • Persistent high blood sugar leads to vessel leakage, swelling, blockage, or abnormal vessel growth, gradually impairing vision.
• Silent and Progressive Nature: DR is often asymptomatic in its early stages and causes no pain or obvious warning signs. 
• • Vision loss is gradual and painless, which delays diagnosis until damage becomes irreversible, making early screening critical.
• India’s Public Health Burden: India is the “Diabetes Capital of the World”, with about 101 million diabetics and 136 million pre-diabetics. 
  • The prevalence of DR is around 12.5%, and nearly 4% (about 40 lakh people) suffer from Vision-Threatening Diabetic Retinopathy (VTDR).
• Low Awareness and Screening Gap: Nearly 85% of people with diabetes are unaware that the disease can damage vision and therefore do not undergo regular retinal examination. 
  • As a result, only a small fraction of VTDR cases receive timely treatment.
• Human and Economic Cost: DR is a leading cause of blindness among working-age adults, causing severe loss of quality of life, productivity, and independence. 
  • India loses about 2.86 million Quality-Adjusted Life Years (QALYs) annually due to diabetes-related vision loss, with nearly ₹50,000 crore lost each year in productivity.
• Healthcare System Constraints: Despite the large burden, India has only about 1,900 trained retina specialists, making universal specialist-based screening impractical and highlighting the need for technology-enabled, community-level solutions.
• Preventable Yet Neglected Disease: DR is one of the most preventable causes of blindness. 
  • Annual retinal screening, good blood sugar, blood pressure, and lipid control, early referral, and timely treatment can prevent severe vision loss in most cases.
• Relevance of AI-Based Screening: The combination of high diabetes prevalence, low awareness, specialist shortage, and asymptomatic progression makes DR particularly suited for Artificial Intelligence–driven community screening models, enabling early detection at scale.

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