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AI tools are quietly reshaping Indian healthcare. From foetal ultrasound dating and high-risk-pregnancy guidance to virtual autopsies and clinical chatbots, they are matching expert accuracy while accelerating workflows. Yet their promise comes entwined with the systemic challenges of data and automation bias, privacy, and weak regulation, often exacerbated by the sensitivities of the healthcare sector itself.

Researchers at IIT-Madras and the Translational Health Science and Technology Institute in Faridabad are developing an artificially intelligent (AI) model to use ultrasonography pictures to predict the age of a growing foetus. Called Garbhini-GA2, the model was trained on scans from about 3,500 pregnant women who had visited the Gurugram Civil Hospital in Haryana. Each scan labelled different parts of the foetus, its size, and its weight — measures that can be used to predict a foetus’s age.

After the training, team members tested it with (unlabelled) scans from 1,500 pregnant women who had visited the same hospital and around 1,000 pregnant women who had visited the Christian Medical College Vellore. They found Garbhini-GA2 erred on the age of the foetus by only half a day. This is a significant improvement over the most common method today: using Hadlock’s formula. Because the formula is based on data from Caucasian populations, it has been known to miss the age of the foetus in India by up to seven days, according to the IIT-Madras team.

The team now plans to test its model in datasets from around India.

This is just a glimpse of how AI tools are quietly reshaping Indian healthcare. From foetal ultrasound dating and high-risk-pregnancy guidance to virtual autopsies and clinical chatbots, they are matching expert accuracy while accelerating workflows. Yet their promise comes entwined with the systemic challenges of data and automation bias, privacy, and weak regulation, often exacerbated by the sensitivities of the healthcare sector itself.

Almost half of all pregnancies in Indian women are high-risk pregnancies (HRPs), according to a 2023 study in the Journal of Global Health. In an HRPs, there is a high chance of the mother and the newborn taking ill or dying. The conditions that cause these outcomes include severe anaemia, high blood pressure, pre-eclampsia, and hypothyroidism. The risks are higher for women with no formal education, those from rural areas, and those belonging to marginalised social groups.

Experts say routine monitoring is the best way to reduce maternal and perinatal mortality in HRPs. In rural areas, this task is often carried out by auxiliary nurse-midwives (ANMs), female health workers who are the first point of contact between a pregnant woman and the medical system. ANMs are trained by medical professionals to recognise HRPs and advise women on their options.

Mumbai-based NGO ARMMAN started such a training programme in 2021 in partnership with UNICEF and the Governments of Telangana and Andhra Pradesh. It has been training healthcare professionals, including ANMs, in “end-to-end management of HRPs,” ARMMAN’s director of innovation Amrita Mahale said.