Health and Me

Rachel V Thomas

UP partners with Wadhwani AI to improve TB care, telemedicine, maternal and child health

The Uttar Pradesh Government today announced a partnership with Wadhwani AI to develop a roadmap for deploying a suite of AI-powered solutions across the state’s public health programs.

The partnership will advance the deployment of seven AI-powered solutions, such as:

<ul><li><a href="https://www.healthandme.com/health/tuberculosis">tuberculosis</a> care and management </li></ul><ul><li>telemedicine </li></ul><ul><li>eye health </li></ul><ul><li>maternal and child health </li></ul><ul><li>equipping frontline health workers with data-driven tools </li></ul>

Wadhwani AI will serve as a technical partner to the state, supporting the deployment of AI-driven tools aligned with the government’s public health priorities.

The collaboration aligns with the UP AI Mission -- a three-year initiative launched by the UP Government to build a state-led AI ecosystem and accelerate the use of AI across sectors, including governance, healthcare, and agriculture.

“AI offers a promising opportunity to further enhance efforts by supporting frontline health workers, improving early disease detection, and enabling more informed clinical decision-making,” said Amit Kumar Ghosh (IAS), Additional Chief Secretary, Medical Health, Family Welfare, and Medical Education in Uttar Pradesh. 

“Through this partnership with Wadhwani AI, we look forward to adopting and deploying AI-driven tools across our health programs and progressively expanding the use of these solutions to further strengthen service delivery and improve health outcomes across the state,” Ghosh added.

<ul><li>In tuberculosis care, the Cough Against TB (CATB) mobile phone-based screening application will enable frontline healthcare workers to identify individuals with presumptive pulmonary TB by analyzing cough sounds and accompanying symptoms, enabling early detection even in community settings. </li></ul>

Vulnerability Mapping for Tuberculosis (VMTB) will use geospatial AI analytics to identify high-risk locations by analyzing TB program data alongside multiple environmental and health indicators, helping health authorities prioritize targeted interventions and active case-finding activities.   

The Prediction of Adverse TB Outcomes (PATO), an AI-powered risk stratification tool, will help identify patients at higher risk of adverse outcomes at the onset of TB treatment and facilitate prompt, targeted, and effective interventions that, over time, will help lower mortality rates and prevent drug-resistant TB.  

<ul><li>In telemedicine, the Clinical Decision Support System (CDSS) will enable clinicians to access structured patient information and offer AI-assisted differential diagnosis recommendations during consultations, supporting the quality and consistency of care delivery across primary healthcare settings. </li></ul>

<ul><li>The collaboration will also include the deployment of Health Vaani, a voice- and text-based knowledge assistant which will provide frontline health workers with instant access to government-approved health guidelines, enabling quicker decision-making and more consistent service delivery at the community level. </li></ul>

<ul><li>To address the growing burden of diabetes-related vision complications, the partnership will also deploy MadhuNetrAI, an AI-enabled screening solution that will analyze retinal images to detect diabetic retinopathy and support early referral for specialist care, particularly in resource-constrained settings where specialist availability may be limited.</li></ul>

<ul><li>In maternal and newborn health, Shishu Maapan, an AI-powered newborn anthropometry tool, will enable frontline health workers to capture accurate newborn measurements using a smartphone during home-based newborn care visits. </li></ul>The solution measures baby weight and other anthropometric indicators to identify newborns at risk of growth complications during the critical early weeks after birth, enabling timely referral and intervention.

“The solutions being deployed span the continuum of health delivery from identifying high-risk communities to supporting ASHA workers during field visits, to enabling early disease detection through AI-assisted analysis,” said Dr. Neeraj Agrawal, Chief Program Officer, Wadhwani AI.

"As the partnership progresses, we look forward to expanding this work and supporting additional AI solutions that can further strengthen health systems and improve outcomes at scale," he added.

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Wadhwani AI

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Tuberculosis

telemedicine

eye health

UP AI Mission

maternal and child health

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The Uttar Pradesh Government today announced a partnership with Wadhwani AI to develop a roadmap for deploying a suite of AI-powered solutions across the state’s public health programs.  The partnership will advance the deployment of seven AI-powered solutions, such as:   tuberculosis care and management telemedicine eye health maternal and child health equipping frontline health workers with data-driven tools Wadhwani AI will serve as a technical partner to the state, supporting the deployment of AI-driven tools aligned with the government’s public health priorities. The collaboration aligns with the UP AI Mission -- a three-year initiative launched by the UP Government to build a state-led AI ecosystem and accelerate the use of AI across sectors, including governance, healthcare, and agriculture. “AI offers a promising opportunity to further enhance efforts by supporting frontline health workers, improving early disease detection, and enabling more informed clinical decision-making,” said Amit Kumar Ghosh (IAS), Additional Chief Secretary, Medical Health, Family Welfare, and Medical Education in Uttar Pradesh. “Through this partnership with Wadhwani AI, we look forward to adopting and deploying AI-driven tools across our health programs and progressively expanding the use of these solutions to further strengthen service delivery and improve health outcomes across the state,” Ghosh added.The AI-powered Solutions In tuberculosis care, the Cough Against TB (CATB) mobile phone-based screening application will enable frontline healthcare workers to identify individuals with presumptive pulmonary TB by analyzing cough sounds and accompanying symptoms, enabling early detection even in community settings. Vulnerability Mapping for Tuberculosis (VMTB) will use geospatial AI analytics to identify high-risk locations by analyzing TB program data alongside multiple environmental and health indicators, helping health authorities prioritize targeted interventions and active case-finding activities.   The Prediction of Adverse TB Outcomes (PATO), an AI-powered risk stratification tool, will help identify patients at higher risk of adverse outcomes at the onset of TB treatment and facilitate prompt, targeted, and effective interventions that, over time, will help lower mortality rates and prevent drug-resistant TB.  In telemedicine, the Clinical Decision Support System (CDSS) will enable clinicians to access structured patient information and offer AI-assisted differential diagnosis recommendations during consultations, supporting the quality and consistency of care delivery across primary healthcare settings.  The collaboration will also include the deployment of Health Vaani, a voice- and text-based knowledge assistant which will provide frontline health workers with instant access to government-approved health guidelines, enabling quicker decision-making and more consistent service delivery at the community level.  To address the growing burden of diabetes-related vision complications, the partnership will also deploy MadhuNetrAI, an AI-enabled screening solution that will analyze retinal images to detect diabetic retinopathy and support early referral for specialist care, particularly in resource-constrained settings where specialist availability may be limited.  In maternal and newborn health, Shishu Maapan, an AI-powered newborn anthropometry tool, will enable frontline health workers to capture accurate newborn measurements using a smartphone during home-based newborn care visits.  The solution measures baby weight and other anthropometric indicators to identify newborns at risk of growth complications during the critical early weeks after birth, enabling timely referral and intervention.  “The solutions being deployed span the continuum of health delivery from identifying high-risk communities to supporting ASHA workers during field visits, to enabling early disease detection through AI-assisted analysis,” said Dr. Neeraj Agrawal, Chief Program Officer, Wadhwani AI."As the partnership progresses, we look forward to expanding this work and supporting additional AI solutions that can further strengthen health systems and improve outcomes at scale," he added.