Computational Approaches for Predicting Preterm Birth and Newborn Outcomes.
Clin Perinatol
; 51(2): 461-473, 2024 Jun.
Article
en En
| MEDLINE
| ID: mdl-38705652
ABSTRACT
Preterm birth (PTB) and its associated morbidities are a leading cause of infant mortality and morbidity. Accurate predictive models and a better biological understanding of PTB-associated morbidities are critical in reducing their adverse effects. Increasing availability of multimodal high-dimensional data sets with concurrent advances in artificial intelligence (AI) have created a rich opportunity to gain novel insights into PTB, a clinically complex and multifactorial disease. Here, the authors review the use of AI to analyze 3 modes of data electronic health records, biological omics, and social determinants of health metrics.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Nacimiento Prematuro
/
Registros Electrónicos de Salud
Límite:
Female
/
Humans
/
Newborn
/
Pregnancy
Idioma:
En
Revista:
Clin Perinatol
Año:
2024
Tipo del documento:
Article