Computational Approaches for Predicting Preterm Birth and Newborn Outcomes.
Clin Perinatol
; 51(2): 461-473, 2024 Jun.
Article
in 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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Artificial Intelligence
/
Premature Birth
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Electronic Health Records
Limits:
Female
/
Humans
/
Newborn
/
Pregnancy
Language:
En
Journal:
Clin Perinatol
Year:
2024
Document type:
Article
Country of publication: