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Future of machine learning in paediatrics.

Sarah Ln Clarke1,2,3, Kevon Parmesar2, Moin A Saleem4,5

  • 1MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Archives of Disease in Childhood
|July 24, 2021
PubMed
Summary
This summary is machine-generated.

Machine learning (ML), a form of artificial intelligence (AI), analyzes health data to improve pediatric care. This technology aids clinical decisions, workforce efficiency, and drug development in pediatrics.

Keywords:
healthcare economics and organisationsinformation technology

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Healthcare Technology

Background:

  • Machine learning (ML) and artificial intelligence (AI) are increasingly used in daily life for data analysis and predictive modeling.
  • Healthcare is beginning to leverage ML/AI, as recognized by the 'National Health Service Long Term Plan 2019'.
  • Paediatric services face growing demands due to workforce challenges, increased attendance, and patient complexity.

Purpose of the Study:

  • To review the potential impact of ML on various aspects of paediatric care.
  • To explore how ML can address challenges in paediatric healthcare delivery.
  • To highlight ML applications from workforce efficiency to precision medicine in paediatrics.

Main Methods:

  • Review of current literature and applications of ML in healthcare.
  • Analysis of ML's role in data interpretation and predictive modeling within paediatrics.
  • Examination of ML's potential across clinical decision-making, workforce efficiency, precision medicine, and drug development.

Main Results:

  • ML offers significant potential to enhance efficiency and decision-making in paediatric healthcare.
  • Applications range from improving diagnostic accuracy to personalizing treatments.
  • ML can aid in developing new drugs and optimizing paediatric service delivery.

Conclusions:

  • ML is poised to transform paediatric care by improving efficiency, aiding clinical decisions, and advancing precision medicine.
  • The integration of ML/AI is crucial for meeting the growing demands on paediatric services.
  • Further research and implementation of ML are essential for the future of paediatric healthcare.