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A pilot study to implement artificial intelligence-enabled, point-of-care obstetric ultrasound for gestational age estimation in Zambia: An evaluation protocol
- Erika Gazzetta,
- Tulani Francis L. Matenga,
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Stephanie Martin,
Roles Conceptualization, Methodology, Supervision, Writing – review & editing
Affiliation Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
⨯ - Nelly Mandona,
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Rassil Barada,
Roles Conceptualization, Data curation, Methodology, Project administration, Supervision, Writing – review & editing
Affiliation Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
⨯ - Modesta Chileshe,
- Elizabeth Stringer,
- Manze Chinyama,
- Beene Chembo,
- Harmony Chi,
- Angel Mwiche,
- Selia Ng’anjo,
- Jeffrey S.A. Stringer,
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Benjamin H. Chi ,
Roles Conceptualization, Data curation, Methodology, Supervision, Writing – original draft, Writing – review & editing
* E-mail: bchi@med.unc.edu
Affiliation Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
⨯ - Margaret Kasaro
https://orcid.org/0000-0002-0378-802X
A pilot study to implement artificial intelligence-enabled, point-of-care obstetric ultrasound for gestational age estimation in Zambia: An evaluation protocol
- Erika Gazzetta,
- Tulani Francis L. Matenga,
- Stephanie Martin,
- Nelly Mandona,
- Rassil Barada,
- Modesta Chileshe,
- Elizabeth Stringer,
- Manze Chinyama,
- Beene Chembo,
- Harmony Chi
- Published: September 11, 2026
- https://doi.org/10.1371/journal.pone.0357962