mlHealth360, Madhya Pradesh Government Launch AI Radiology Pilot in 10 District Hospitals

The program, announced on April 9, aims to enhance diagnostic accuracy, reduce reporting delays, and support faster clinical decisions in public hospital settings.

mlHealth360 has signed a memorandum of understanding with the Government of Madhya Pradesh to pilot AI-powered radiology solutions in ten district hospitals across the state.

The program, announced on April 9, aims to enhance diagnostic accuracy, reduce reporting delays, and support faster clinical decisions in public hospital settings.

Central to the deployment is mlHealth360’s proprietary Scaida AI platform, which detects and triages abnormalities in CT scans, provides real-time decision support, and generates standardized radiology reports. The platform integrates with existing hospital systems, including PACS and RIS, ensuring minimal disruption to current workflows while adding AI-led efficiency.

The cloud-based solution is designed for scale, featuring remote expert connectivity and India-based data residency, making it suitable for high-volume district hospitals and resource-constrained environments.

“This collaboration allows us to take a meaningful step toward integrating AI into mainstream public healthcare delivery,” said Kumar Surender Sinwar, Founder and CEO of mlHealth360. He noted that the focus is on embedding the technology into workflows and delivering measurable value for clinicians in high-burden settings.

The AI-driven system is expected to enhance early detection of conditions such as stroke, hemorrhage, trauma, and tumors. By automatically prioritizing urgent cases, Scaida AI could help clinicians respond more quickly to critical patients and reduce referrals to tertiary care centers.

Dr. Narendra Gupta from the state Health Department said the initiative aligns with Madhya Pradesh’s broader goal of building a more efficient, technology-enabled healthcare ecosystem. AI-supported radiology is expected to strengthen district-level capabilities, expand access to diagnostics, and reduce the need for patients in remote areas to travel long distances for specialist care.

The rollout will follow a phased approach, starting with site readiness assessments and system integration, followed by clinician training and full operational deployment over the coming months. The pilot will also serve as a potential blueprint for a statewide implementation depending on performance outcomes.

Stay tuned for more such updates on Digital Health News