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    Rwanda Tests AI-Enabled Ultrasound Tools for Community Health Workers

    OneAfricaYTBy No Comments3 Mins Read
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    Rwanda is piloting AI-powered point-of-care ultrasound (POCUS) tools for effective pregnancy monitoring and to strengthen early detection of complications at the primary healthcare level.

    ALSO READ: How Rwandan ‘virtual hospital’ is changing maternal, newborn healthcare

    This was announced by Yves Iradukunda, the Minister of State at the Ministry of ICT and Innovation, on October 16, during a session with senators on the use of artificial intelligence in the development of the country.


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    The project, he said, aims to equip community health workers, nurses, and midwives with easy-to-use, portable ultrasound devices expected to improve maternal and neonatal outcomes, especially in remote areas.

    ALSO READ: How Rwanda enhances mother, child health through community engagement

    These AI-enabled tools allow health workers with minimal training to accurately estimate gestational age and identify high-risk pregnancies, supporting timely referrals and improved care for mothers and babies.

    “This is a portable tool that even a community health worker can carry in their bag. It is powered by AI and can be used to check a baby’s health–such as whether organs are developing properly and whether the baby is healthy based on key metrics,” Iradukunda said.

    How the tool is used

    Simple blind sweep: Health workers perform a straightforward ultrasound scan without needing specialized expertise.

    AI image interpretation: The AI system automatically analyses the images to estimate gestational age and detect pregnancy risks.

    Biometric analysis: The tool measures foetal parameters such as head circumference and femur length, providing accurate results in under 10 minutes.

    Low training requirement: Designed for rapid adoption, requiring less than one day of training.

    Key benefits for maternal health are enabling early identification and referral for complications such as preterm birth or foetal growth restriction.

    For the health system, the development is expected to increase antenatal care attendance and improve referral accuracy.

    Iradukunda underscored that the project focuses on empowering frontline health workers to detect abnormalities early and refer mothers to health centres or hospitals for appropriate care.