AI-POCUS for Maternal and Neonatal Health in Ethiopia

Summary

Maternal and neonatal health remains one of the most pressing global health challenges, particularly in low- and middle-income countries (LMICs). Ethiopia continues to face a high burden, with maternal mortality estimated at 195 per 100,000 live births, neonatal mortality at 27 per 1,000 live births, and perinatal mortality rates ranging from 37‰ to 124‰ depending on the level of care. These outcomes remain substantially higher than the targets set under the United Nations Sustainable Development Goals (SDGs) for 2030.

The World Health Organization (WHO) recommends that all pregnant women receive at least one ultrasound scan before 24 weeks of gestation, yet nearly two-thirds of women worldwide-especially in LMICs-lack access to this service. Barriers include high costs of ultrasound machines, limited technical expertise, and shortages of skilled sonographers in rural primary care.

Artificial Intelligence-driven Point-of-Care Ultrasound (AI-POCUS) represents a promising innovation to expand prenatal imaging in resource-constrained settings by equipping frontline health workers with AI-supported diagnostic capabilities. This study, conducted under the Tsinghua University BRIGHT (Bringing Research to Impact for Global Health at Tsinghua) program, will evaluate the clinical effectiveness, feasibility, cost, and scalability of AI-POCUS in rural Ethiopia. A three-arm cluster randomized controlled trial will compare two AI-enabled ultrasound technologies-BabyChecker (Netherlands) and a China-developed AI-POCUS device-against standard antenatal care without ultrasound. Findings will generate robust clinical and policy-relevant evidence to guide the sustainable implementation of AI-enabled maternal health interventions in sub-Saharan Africa.

Conditions

• Pregnancy
• Pregnancy Complications
• Preterm Birth
• Fetal Growth Restriction
• Stillbirth and Fetal Death
• Pregnancy Abnormal

Interventions

DEVICE

AI-POCUS (BabyChecker, Delft Imaging)

A portable AI-driven ultrasound system developed by Delft Imaging (Netherlands). The device integrates fetal position, amniotic fluid volume, and biparietal diameter measurements, with built-in diagnostic suggestions and risk alerts. Primary healthcare workers, after brief training, use it for antenatal screening, complication detection, and referral decision-making.

DEVICE

AI-POCUS (Edan, China)

An AI-POCUS device developed by Edan (China), capable of analyzing blind ultrasound sweeps to extract fetal diagnostic parameters and assist in early risk identification. It supports clinical decision-making for antenatal care.

Sponsors & Collaborators

• Debre Berhan University

  collaborator OTHER

• Tsinghua University

  lead OTHER

Principal Investigators

• Kun TANG, Associate Professor · Tsinghua University

Study Design

Allocation

RANDOMIZED

Purpose

SCREENING

Masking

SINGLE

Model

PARALLEL

Eligibility

Min Age

15 Years

Max Age

49 Years

Sex

FEMALE

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2025-09-30

Primary Completion

2026-03-31

Completion

2026-08-31

Countries

• Ethiopia

Study Locations