Artificial Intelligence-Assisted Fetal Ultrasound in Low-Resource Settings: Opportunities, Challenges, and Future Directions
Aug 08,26 | 01:31 EST
Artificial intelligence (AI) is a promising solution to enhance fetal ultrasound access in low-resource settings, addressing shortages of trained staff, limited infrastructure, and unequal diagnostic imaging. This review examines AI's clinical applications, implementation experiences, challenges, and future prospects in fetal ultrasound. AI can support various stages, including gestational age estimation, automated biometry, image quality assessment, anomaly detection, fetal monitoring, image enhancement, and edge deployment, demonstrating encouraging diagnostic performance and potential for task-shifting to non-specialist healthcare providers. However, challenges include underrepresentation of low-resource populations in training datasets, limited prospective validation, infrastructure constraints, training needs, and unresolved regulatory and ethical issues. Future research should focus on local datasets, multicenter validation, resource-efficient AI models, robust regulations, and health economic evaluations to ensure equitable access to quality antenatal imaging and improved maternal and fetal healthcare.
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