How AI is changing the face of maternal care in remote areas

BabyChecker offers a cost-effective and efficient solution for early pregnancy risk detection. [Courtesy]

Artificial Intelligence (AI) is transforming maternal and child healthcare in remote regions of Africa, offering innovative solutions to the challenges faced by underserved communities.

Across Africa, where maternal mortality rates remain alarmingly high due to limited access to healthcare, AI-powered technologies are stepping in to bridge the gap.

One such breakthrough is BabyChecker, an AI-powered portable ultrasound device developed by Delft Imaging, a Netherlands-based social enterprise.

Unveiled during the Africa Health Agenda International Conference (AHAIC) 2025 in Kigali, Rwanda, BabyChecker represents a significant milestone in maternal healthcare.

Designed specifically for low- and middle-income countries, BabyChecker offers a cost-effective and efficient solution for early pregnancy risk detection.

The portable device consists of a smartphone, an ultrasound probe, a mobile application, and a user instruction card.

Unlike conventional ultrasound machines, which require trained professionals, BabyChecker leverages AI to analyse ultrasound images.

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The solution enables community health workers (CHWs) with minimal training to conduct ultrasound screenings easily.

Akshay Rajagopal, BabyChecker Project Manager at Delft Imaging, explains that the technology analyses obstetric ultrasound scans to identify gestational age and high-risk pregnancies, such as fetal malposition, placenta previa, and multiple pregnancies.

Delft Imaging has a long history in screening solutions, dating back to the early 20th century when it pioneered X-ray screening for tuberculosis (TB) in the Netherlands.

Over time, Delft Imaging transitioned to digital health solutions, incorporating AI to provide more portable and effective screening tools for diseases, such as TB and maternal health complications.

BabyChecker targets communities with limited access to healthcare due to high maternal and child deaths.

“With a long history of providing solutions for diseases in remote villages, we developed the idea of BabyChecker to address the high maternal mortality that can be easily prevented with timely intervention,” explained Akshay.

“BabyChecker is not replacing standard ultrasound; it is meant to provide ultrasound services in areas where expecting mothers cannot access these services,” he added.

While Delft Imaging has been active in more than 85 countries, BabyChecker has been deployed in over 10 nations in collaboration with technical advisors, funders, and local partners to integrate AI into maternal healthcare.

BabyChecker has been successfully piloted and commercialised in multiple regions, including Sub-Saharan Africa, Central and Latin America, and Pakistan.

The technology is designed for use by community health workers and consists of an ultrasound probe connected to a mobile phone running the BabyChecker app.

Once completed, AI processes the ultrasound images in just five seconds, providing critical insights.

The results are displayed on the smartphone as traffic lights: green, yellow, and red. The green signal indicates that pregnancy is progressing well, and the woman can continue antenatal care.

Yellow indicates potential complications, but they are not high-risk, while red signals a risky pregnancy that requires immediate referral to save both mother and child. “The results of the scan determine the care for the pregnancy; for example, when the scan indicates yellow, the pregnant woman must visit the hospital within two weeks for a check-up and management,” explained the expert.

The traffic light system is adaptable to various national health protocols, ensuring relevance across countries. Akshay said the application would soon include other risk parameters.

Currently, in most remote areas, community health workers scan women using only their bare hands, often leading to inaccurate results, delayed referrals, and an increased risk of death.

The device has contributed to a rise in antenatal care (ANC) visits, particularly during the first trimester, when many women may not yet be aware of their pregnancy. “In Kenya, the AI technology was adopted in October 2024, and at least 500 screenings have already been conducted,” Akshay stated.

Since its initial rollout, over 9,000 scans have been performed globally by more than 200 community health workers.

Akshay emphasised that BabyChecker is designed for rural and remote settings, requiring no internet connection or electricity. This makes it an ideal solution for low-resource environments where maternal mortality remains alarmingly high. “By equipping CHWs with AI-driven screening tools, we can significantly reduce maternal mortality,” he explained.

In Kenya, around 6,000 to 8,000 women die during childbirth every year, with common causes of maternal deaths being obstetric haemorrhage, non-obstetric complications/indirect maternal deaths, and hypertensive disorders associated with pregnancy.

When fully charged, the app can conduct 30 to 50 scans.