Health Ministry Accelerates AI Adoption in Public Healthcare

The move strengthens India’s digital health infrastructure by placing research, model testing, and real-world adoption under specialised hubs.

The Ministry of Health and Family Welfare is scaling AI-led interventions across the public health system, designating AIIMS Delhi, PGIMER Chandigarh, and AIIMS Rishikesh as Centres of Excellence (CoEs) to advance the development and deployment of AI-based healthcare solutions.

The move strengthens India’s digital health infrastructure by placing research, model testing, and real-world adoption under specialised hubs.

The Ministry is working with multiple national institutions—including the Central Tuberculosis Division, National Centre for Disease Control, CDAC-Mohali, ICMR, MeitY, Ministry of Higher Education, IISc, and National Health Systems Resource Centre—along with technical support from Wadhwani AI. These collaborations are driving projects across diagnostics, telemedicine optimisation, and population-scale screening.

Among the key deployments is MadhuNetrAI, an AI-based diabetic retinopathy (DR) identification solution that enables non-specialist health workers to conduct frontline DR screening. The model analyzes retinal fundus images to classify DR severity and flag urgent cases for specialist referral. The tool has been rolled out across 38 facilities in 11 states, supporting screening of over 14,000 retinal images and benefiting more than 7,100 patients.

The Ministry has also integrated an AI-powered Clinical Decision Support System (CDSS) into the national telemedicine platform eSanjeevani. The tool standardises patient complaint entries and generates AI-driven differential diagnosis suggestions for clinicians. Between April 2023 and November 2025, CDSS has contributed to 282 million eSanjeevani consultations, strengthening clinical consistency across health and wellness centres.

For tuberculosis elimination, the Ministry is deploying the Cough Against TB (CATB) solution to support community-level pulmonary TB screening. In regions where it is active, CATB has improved case detection by 12–16%, compared to conventional screening methods. From March 2023 to November 30, 2025, the tool has screened more than 1.62 lakh individuals.

All AI deployments adhere to national digital and data protection frameworks, including MeitY’s AI Governance Guidelines, ICMR’s ethical guidance for biomedical AI, the IT Act 2000, the Digital Personal Data Protection Act 2023, and the Information Security Policy for Healthcare.

Stay tuned for more such updates on Digital Health News