Clinical Pearl: Artificial Intelligence, Machine Learning Models in Neonatology: Neonatal Acute Kidney Injury 

Joseph R. Hageman, MD, Lolita Alkureishi, MD, Walid Hussain, MD, Mitchell Goldstein, MD, MBA, CML

Artificial intelligence (AI) and machine learning (ML) models are being utilized in several clinical issues in neonatology, including necrotizing enterocolitis, retinopathy of prematurity, and now acute kidney injury (AKI) (1-5). 

AI is a “branch of computer science that develops systems capable of human-like intellectual processes to solve problems. ML, a subset of AI, uses large data sets and some human input (adding or changing parameters) to teach itself patterns and to make predictions (6)”. 

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References: 

  1. McElroy SJ and Lueschow SR> State of the art on machine learning and artificial learning in the study of neonatal necrotizing enterocolitis . Frontiers in Pediatrics 2023. Doi: 10.3389/fled.2023.1182597
  2. Starr MC, Charlton JR, Gulliet R et al. Advances in neonatal kidney injury. Pediatrics 2021; 148(5);32021051220. 
  3. Raina R, Nada A, Aly I et al. Ariticial intelligence in early detection of pediatric/neonatal acute kidney injury: current status and future directions. Pediatr Nephrol. 2023; DOI: 10.1007/s00467-023-06191-7
  4. Coleman C, Tambay Perez A, Selewski DT, Steflik HJ. Neonatal Acute Kidney Injury. Front Pediatr. 2022 April 7;10:842544. doi: 10.3389/fped.2022.842544. PMID: 35463895; PMCID: PMC9021424. 
  5. Jeong H, Kamaleswaran R. Pivotal challenges in artificial intelligence and machine leaning applications for neonatal care.Semin Fetal Neonatal Med. 2022;Oct,27(5):101393. Epub.2022 October 13. Doi: 10.1016/jsiny.2022.101393. Epub 2022 October 13.
  6. Shah S, Slaney E, VerHage E et al. Application of artificial intelligence in the early detection of retinopathy of prematurity: Review of the literature. Neonatology 2023; 120(5):558-565. https://doi.org/10.1159/000531441. 
  7. Guide to unlocking value in EHR & EMR using. October 4, 2023. AI https://www.hippocraticpost.com/innovation/guide-to-unlocking-value-in-ehr-emr-using-ai/ Accessed January 29, 2024. 

Disclosures: The authors have no disclosures 

Corresponding Author
Joseph R. Hageman, MD

Joseph R. Hageman, MD
Senior Clinician Educator
Pritzker School of Medicine
University of Chicago
MC6060
5841 S. Maryland Ave.
Chicago, IL 60637
Phone: 773-702-7794
Fax: 773-732-0764
Email: jhageman@peds.bsd.uchicago.edu

Lolita Alkureishi, MD

Lolita Alkureishi, MD
Associate Professor of Pediatrics
Assistant Director, Ambulatory Care Residency Program
Director, Pediatric Clerkship
University of Chicago
Chicago, IL

Walid Hussain, MD

Walid Hussain, MD
Associate Professor of Pediatrics
The University of Chicago
Department of Pediatrics
Email: whussain1@uchicago.edu

Dr. Mitch Goldstein, MD

Mitchell Goldstein, MD
Professor of Pediatrics
Loma Linda University School of Medicine
Division of Neonatology
Department of Pediatrics
Email: mgoldstein@llu.edu

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