Researchers have developed an India-specific artificial intelligence model to precisely determine the gestational age of a foetus in the second and third trimester of pregnancy.
The model has been designed by researchers at the Indian Institute of Technology Madras and the Translational Health Science and Technology Institute, Faridabad.
It is part of an interdisciplinary group for advanced research on birth outcomes — the DBT India initiative (GARBH-Ini) programme. The Garbhini-GA2 is the first late-trimester GA estimation model to be developed and validated using Indian population data. Currently, models used for the Western population are in use which could prove erroneous when applied in the later part of pregnancy due to variations in the growth of the foetus in the Indian population, the researchers say.
The Garbhini-GA2 accurately estimates the foetus’ age, reducing error by almost three times.
Appropriate care
The Indian data would help to provide appropriate care for pregnant women and determine the precise date of birth, thus reducing maternal and infant mortality rates.
Secretary, Department of Biotechnology, Rajesh Gokhale said GARB-Ini, the department’s flagship programme, was being validated across the country.
Several investigators, including Himanshu Sinha, associate professor, Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, IIT Madras, Shinjini Bhatnagar, principal investigator of the programme and a distinguished professor at THSTI, were involved in the project.
The findings were published in the peer-reviewed Lancet Regional Health Southeast Asia.
Mr. Sinha said advanced data science and AI/ML techniques were used to build tools to predict unfavourable birth outcomes and the first step is to develop accurate GA models that perform significantly better than currently used models designed using western populations.
End-to-end partnership
Ms. Bhatnagar said the application of sophisticated data science tools was not sufficient. Ensuring that technological advancements yield tangible benefits in the clinical realm lies in the end-to-end partnership between clinicians and data scientists. “Such collaboration ensures that the development of solutions is not only technically sound but also clinically relevant and seamlessly integrated into healthcare workflows,” she said.
The study was conducted in partnership with Gurugram Civil Hospital, Gurugram, Safdarjung Hospital, New Delhi, Christian Medical College, Vellore and Pondicherry Institute of Medical Sciences, Puducherry.
Additional funding for the project came from the Robert Bosch Centre for Data Science and Artificial Intelligence and the Centre for Integrative Biology and Systems Medicine at IIT Madras.
