State of the art review on machine learning and artificial intelligence in the study of neonatal necrotizing enterocolitis

Steven J McElroy; Shiloh R Lueschow

doi:10.3389/fped.2023.1182597

State of the art review on machine learning and artificial intelligence in the study of neonatal necrotizing enterocolitis

Front Pediatr. 2023 May 26:11:1182597. doi: 10.3389/fped.2023.1182597. eCollection 2023.

Authors

Steven J McElroy¹, Shiloh R Lueschow²

Affiliations

¹ Department of Pediatrics, University of California Davis, Sacramento, CA, United States.
² Stead Family Department of Pediatrics, University of Iowa, Iowa City, IA, United States.

Abstract

Necrotizing Enterocolitis (NEC) is one of the leading causes of gastrointestinal emergency in preterm infants. Although NEC was formally described in the 1960's, there is still difficulty in diagnosis and ultimately treatment for NEC due in part to the multifactorial nature of the disease. Artificial intelligence (AI) and machine learning (ML) techniques have been applied by healthcare researchers over the past 30 years to better understand various diseases. Specifically, NEC researchers have used AI and ML to predict NEC diagnosis, NEC prognosis, discover biomarkers, and evaluate treatment strategies. In this review, we discuss AI and ML techniques, the current literature that has applied AI and ML to NEC, and some of the limitations in the field.

Keywords: artificial intelligence (AI); biomarker discovery; disease modeling; machine learning (ML); necrotizing enterocolitis (NEC).

Publication types

Review

Grants and funding

SRL is supported by the University of Iowa Stead Department of Pediatrics. SJM is supported by the National Institute of Health (NIH) grant no. R01DK125415 and the UC Davis Children's Hospital Department of Pediatrics.