India’s Health Ministry has named three premier institutes as “Centres of Excellence (CoE)” for AI and is scaling up AI tools across national public-health programmes, including diabetic-retinopathy screening, TB detection and telemedicine, to improve access, speed up diagnosis and reduce burden on specialists.
Glimpse:
With the CoEs established at AIIMS Delhi, PGIMER Chandigarh and AIIMS Rishikesh, the Ministry is driving development, validation and deployment of AI-powered diagnostic and decision-support tools at scale. Key initiatives include
cfdMadhuNetrAI an AI model for diabetic-retinopathy screening that enables non-specialist health workers to screen using retinal fundus images. Deployments already span 38 facilities across 11 states, screening over 14,000 images to benefit 7,100+ patients.
AI-enabled tools integrated into the national tele-medicine platform eSanjeevani to support standardized data capture and AI-assisted triage/diagnosis recommendations during virtual consultations.
AI solutions under the national TB programme for example, a “Cough Against TB” solution used in community screening to improve case detection, reportedly increasing case yield by 12–16% compared to conventional methods.
On 4 December 2025, MoHFW formally announced a major push to embed AI across India’s public-healthcare delivery system. As part of this effort, three major tertiary-care/research institutions AIIMS Delhi, PGIMER Chandigarh and AIIMS Rishikesh have been designated as AI Centres of Excellence (CoEs). These will spearhead development, clinical validation, and system-wide rollout of AI-driven diagnostic and decision-support tools.
The Ministry is collaborating with multiple technical/public-health bodies such as the Central Tuberculosis Division (CTD), National Centre for Disease Control (NCDC), CDAC-Mohali, Wadhwani AI, and academic institutions to deploy AI tools across disease-screening, diagnostics, tele-health and surveillance.
Among the flagship tools is MadhuNetrAI, an AI model for detecting diabetic retinopathy using retinal imaging. Non-specialist health workers at peripheral and primary-care centres are being trained to use this tool, broadening access to retinal screening in remote or underserved areas. According to the Ministry’s latest update, over 14,000 retinal images have been screened so far across 38 centres, benefiting more than 7,100 patients.
To address clinician shortages and strengthen tele-care, AI-enabled Clinical Decision Support Systems (CDSS) have been integrated with the national virtual-care platform eSanjeevani. Since April 2023, millions of consultations have leveraged AI for triage, differential diagnosis suggestions, and standardized reporting helping improve quality and consistency of care in remote consultations.
Under the national TB-control programme, AI-based tools (including cough analysis and imaging-based screening) are being used to enhance detection rates and speed up diagnosis. One such initiative “Cough Against TB” reportedly increased TB-case detection by 12–16% over conventional screening.
Overall, the Ministry’s roadmap seeks to embed AI not as a niche experiment, but as a core part of public-health infrastructure aiming for scale, equity of access, early detection and prevention, especially for rural and underserved populations.
“AI-powered diagnostics can turn every primary-care centre into a potential screening hub bringing specialized screening and early detection to corners of India that have long lacked access.”
By
HB Team
