Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps
0
Zitationen
21
Autoren
2025
Jahr
Abstract
(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.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.200 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.051 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.416 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.410 Zit.
Autoren
- Jeffrey S. A. Stringer
- Teeranan Pokaprakarn
- Juan Carlos Prieto
- Bellington Vwalika
- Srihari V Chari
- Ntazana Sindano
- Bethany L. Freeman
- Bridget Sikapande
- Nicole D. Armstrong
- Yuri V. Sebastião
- Nelly M. Mandona
- Elizabeth M. Stringer
- Chiraz BenAbdelkader
- Mutinta Mungole
- Filson M. Kapilya
- Nariman Almnini
- Arieska N. Diaz
- Brittany A. Fecteau
- Michael R. Kosorok
- Stephen R. Cole
- Margaret P. Kasaro