A survey of obstetric ultrasound uses and priorities for artificial intelligence-assisted obstetric ultrasound in low- and middle-income countries
Abstract Obstetric ultrasound (OBUS) is recommended as part of antenatal care for pregnant individuals worldwide. To better understand current uses of OBUS in low- and middle-income countries and perceptions regarding potential use of artificial intelligence (AI)-assisted OBUS, we conducted an anony...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-87284-1 |
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| Summary: | Abstract Obstetric ultrasound (OBUS) is recommended as part of antenatal care for pregnant individuals worldwide. To better understand current uses of OBUS in low- and middle-income countries and perceptions regarding potential use of artificial intelligence (AI)-assisted OBUS, we conducted an anonymous online global survey. A total of 176 respondents representing 34 countries participated, including 41% physicians, 49% nurses or midwives, and 6% ultrasound technicians. Most had received OBUS training (72%), reported expertise (60%) and confidence (77%) in OBUS use, and had access to ultrasound (85%). Assessment of gestational age, fetal viability, fetal presentation, and multiple gestation were both the most common OBUS uses and among the most highly prioritized for AI-assisted OBUS development. Most respondents noted ultrasound access was important (84%) and agreed that OBUS improves quality of care (98%) and patient outcomes (97%). Of the 34% expressing reservations associated with using AI-assisted OBUS, healthcare providers not understanding the technology (71%), misdiagnosis (62%), and cost (59%) were the most common. Better understanding the OBUS user, the pregnant individual, and the context, and taking care to ensure responsible, sustainable, and inclusive development and use of AI-assisted OBUS will be critical to successful integration and implementation and to increasing access to OBUS. |
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| ISSN: | 2045-2322 |