AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges-Reference-Cited by-同舟云学术

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AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges

Published:2023-09 Issue: Volume:15 Page:100435
ISSN:2666-5204
Container-title:Resuscitation Plus
language:en
Short-container-title:Resuscitation Plus

Author:

Okada Yohei^ORCID,Mertens Mayli,Liu Nan,Lam Sean Shao Wei,Ong Marcus Eng Hock

Funder

ZOLL Foundation

JSPS

European Commission

Japan Society for the Promotion of Science

International Pediatric Research Foundation

Fukuda Foundation for Medical Technology

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine,Emergency Nursing,Emergency Medicine

Reference94 articles.

1. Artificial intelligence and machine learning;Kühl;Electronic Markets,2022

2. Machine learning-based prediction of clinical outcomes for children during emergency department triage;Goto;JAMA Netw Open,2019

3. Machine learning-based prediction models for accidental hypothermia patients;Okada;J Intensive Care,2021

4. MySurgeryRisk: development and validation of a machine-learning risk algorithm for major complications and death after surgery;Bihorac;Ann Surg,2019

5. Heterogeneous treatment effect analysis based on machine-learning methodology;Gong;CPT Pharmacometrics Syst Pharmacol,2021

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3. Taxonomy development methods regarding patient safety in health sciences – A systematic review;International Journal of Medical Informatics;2024-07

4. Research on optimization of key thermal parameters of the secondary loop of PWR based on improved BP neural network;Annals of Nuclear Energy;2024-07

5. Large language models in food science: Innovations, applications, and future;Trends in Food Science & Technology;2024-06

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