| Title: |
Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps |
| Authors: |
Stringer, Jeffrey S.A.; Pokaprakarn, Teeranan; Prieto, Juan C.; Vwalika, Bellington; Chari, Srihari V.; Sindano, Ntazana; Freeman, Bethany L.; Sikapande, Bridget; Davis, Nicole M.; Sebastião, Yuri V.; Mandona, Nelly M.; Stringer, Elizabeth M.; Benabdelkader, Chiraz; Mungole, Mutinta; Kapilya, Filson M.; Almnini, Nariman; Diaz, Arieska N.; Fecteau, Brittany A.; Kosorok, Michael R.; Cole, Stephen R.; Kasaro, Margaret P. |
| Source: |
Obstetrical & Gynecological Survey ; volume 80, issue 2, page 65-67 ; ISSN 1533-9866 0029-7828 |
| Publisher Information: |
Ovid Technologies (Wolters Kluwer Health) |
| Publication Year: |
2025 |
| Description: |
(Abstracted from JAMA 2024;332:649–657) Gestational age (GA) is critical for guiding obstetric decisions related to antenatal care and delivery. In high-income countries, GA is typically measured via fetal biometry using high-resolution ultrasound machines operated by credentialed sonographers. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1097/ogx.0000000000001375 |
| DOI: |
10.1097/OGX.0000000000001375 |
| Availability: |
https://doi.org/10.1097/ogx.0000000000001375; https://journals.lww.com/10.1097/OGX.0000000000001375 |
| Accession Number: |
edsbas.A5DBC0BC |
| Database: |
BASE |