Artificial intelligence in pediatrics

Lindsey A. Knake; Colin M. Rogerson; Meredith C. Winter; Swaminathan Kandaswamy

doi:10.1016/B978-0-443-15688-5.00017-6

Artificial intelligence in pediatrics

Lindsey A. Knake, Colin M. Rogerson, Meredith C. Winter, Swaminathan Kandaswamy

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Artificial intelligence and machine learning research in pediatrics is exponentially increasing; however, it is still significantly behind adult medical research in the variety of models developed and a number of algorithms currently implemented into clinical practice. The fields of neonatal and pediatric critical care as well as the pediatric sub-specialties of psychiatry, neurology, and pulmonology are currently leading the way in model development. Current work is underway to try to expand successful adult algorithms into pediatric use cases. Future work that is needed to enhance multi-center collaboration and model implementation into clinical practice which includes the need for centralization of multi-institutional databases, increased use of continuous physiologic and genomic data, and clinical implementation of precision medicine using predictive modeling.

Original language	English
Title of host publication	Artificial Intelligence in Clinical Practice
Subtitle of host publication	How AI Technologies Impact Medical Research and Clinics
Publisher	Elsevier
Pages	285-295
Number of pages	11
ISBN (Electronic)	9780443156885
ISBN (Print)	9780443156892
DOIs	https://doi.org/10.1016/B978-0-443-15688-5.00017-6
Publication status	Published - 1 Jan 2023
Externally published	Yes

Keywords

Pediatrics
machine learning
model implementation
neonatology
pediatric critical care
precision medicine
predictive models
unsupervised machine learning

ASJC Scopus subject areas

General Computer Science

Access to Document

10.1016/B978-0-443-15688-5.00017-6

Cite this

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abstract = "Artificial intelligence and machine learning research in pediatrics is exponentially increasing; however, it is still significantly behind adult medical research in the variety of models developed and a number of algorithms currently implemented into clinical practice. The fields of neonatal and pediatric critical care as well as the pediatric sub-specialties of psychiatry, neurology, and pulmonology are currently leading the way in model development. Current work is underway to try to expand successful adult algorithms into pediatric use cases. Future work that is needed to enhance multi-center collaboration and model implementation into clinical practice which includes the need for centralization of multi-institutional databases, increased use of continuous physiologic and genomic data, and clinical implementation of precision medicine using predictive modeling.",

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AU - Rogerson, Colin M.

AU - Winter, Meredith C.

AU - Kandaswamy, Swaminathan

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AB - Artificial intelligence and machine learning research in pediatrics is exponentially increasing; however, it is still significantly behind adult medical research in the variety of models developed and a number of algorithms currently implemented into clinical practice. The fields of neonatal and pediatric critical care as well as the pediatric sub-specialties of psychiatry, neurology, and pulmonology are currently leading the way in model development. Current work is underway to try to expand successful adult algorithms into pediatric use cases. Future work that is needed to enhance multi-center collaboration and model implementation into clinical practice which includes the need for centralization of multi-institutional databases, increased use of continuous physiologic and genomic data, and clinical implementation of precision medicine using predictive modeling.

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KW - machine learning

KW - model implementation

KW - neonatology

KW - pediatric critical care

KW - precision medicine

KW - predictive models

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Artificial intelligence in pediatrics

Abstract

Keywords

ASJC Scopus subject areas

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