Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Artificial Intelligence in Pediatric Emergency Medicine: Applications, Challenges, and Future Perspectives

Lorenzo Di Sarno
* ORCID logo ,
Anya Caroselli
,
Giovanna Tonin
,
Benedetta Graglia
,
Valeria Pansini
,
Francesco Andrea Causio
,
Antonio Gatto
ORCID logo ,
Antonio Chiaretti
Version 1 : Received: 24 April 2024 / Approved: 25 April 2024 / Online: 25 April 2024 (09:00:02 CEST)

How to cite: Di Sarno, L.; Caroselli, A.; Tonin, G.; Graglia, B.; Pansini, V.; Causio, F.A.; Gatto, A.; Chiaretti, A. Artificial Intelligence in Pediatric Emergency Medicine: Applications, Challenges, and Future Perspectives. Preprints 2024, 2024041642. https://doi.org/10.20944/preprints202404.1642.v1 Di Sarno, L.; Caroselli, A.; Tonin, G.; Graglia, B.; Pansini, V.; Causio, F.A.; Gatto, A.; Chiaretti, A. Artificial Intelligence in Pediatric Emergency Medicine: Applications, Challenges, and Future Perspectives. Preprints 2024, 2024041642. https://doi.org/10.20944/preprints202404.1642.v1

Abstract

The dawn of Artificial Intelligence (AI) in healthcare stands as a milestone in medical innovation. A plethora of different medical fields are heavily involved and pediatric emergency medicine is no exception. These new tools do not merely provide more advanced and efficient systems for patients’ diagnosis, management and treatment. They rather concern a strict shift from traditional methods based upon broad categories towards a more personalized healthcare. AI offers many promises in pediatric emergency medicine with a wide range of applications involving clinical decision making, patients’ flows management and prioritization. Main barriers to a widespread diffusion involve technological challenges but also ethical issues and the paucity of extensive datasets in pediatric contexts. We conducted a narrative review structured in two parts. The first part explores the theoretical principles of AI, providing all the necessary background to feel confident with these new state-of-the-art tools. The second part presents an informative analysis of AI models in pediatric emergencies, pointing out the actual applications and challenges until future feasible research perspectives.

Keywords

artificial intelligence; machine learning; pediatrics; deep learning; pediatric emergency medicine

Subject

Medicine and Pharmacology, Pediatrics, Perinatology and Child Health

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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