The Indian government has several initiatives and programs in place to provide quality services to pregnant women and children in order to lower neonatal and infant mortality rates (NMR/IMR) and the maternal mortality ratio (MMR). This is one of the National Health Missions Reproductive, Maternal, Newborn, Child, and Adolescent Health Plus Nutrition (RMNCAH +N) strategys primary priority areas. 

Digitization has grown, as has population mobile phone penetration. Suboptimal dentification of high-risk mothers, difficulties in the classification of low birth weight (LBW) babies and weight measurement, undernutrition leading to 50% child deaths, persistent levels of high anaemia in children, adolescents, pregnant women, and women of reproductive age, and poor quality of maternal care have all been identified as challenges.

To solve these issues, AI-driven solutions might be devised and deployed. AI has created and is developing a variety of AI-driven technologies to solve these issues across the RMNCAH+N spectrum. However, challenges in collecting the right kind of data persist. 

It is necessary to create an application ecosystem that meets the demands of pregnant women, field workers, and the health system in an integrated way. Field workers should be given every opportunity to capitalize on their on-the-ground contacts among user groups.

Maternal health is a complete set of health-care services aimed at preventing negative outcomes, curing diseases, and meeting the needs of pregnant women before, during, and after delivery, as well as babies and preschool children aged birth to five years. 

A targeted and comprehensive approach to services is required to guarantee each womans safe path to motherhood.

 (Source: https://health.economictimes.indiatimes.com/news/health-it/ensuring-safe-motherhood-with-an-ai-integrated-approach/99862617)