Teaching old tools new tricks-preparing emergency medicine for the impact of machine learning-based risk prediction models

Vinyas Harish^#^{1

2

3

4}, Keerat Grewal^#^{5

6}, Muhammad Mamdani^{7

8

9

10

11

12}, Venkatesh Thiruganasambandamoorthy^{13

14

15}

Affiliations

¹ Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
² Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
³ Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
⁴ Vector Institute for Artificial Intelligence, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
⁵ Division of Emergency Medicine, Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁶ Schwartz/Reisman Emergency Medicine Institute, Sinai Health, Toronto, ON, Canada.
⁷ Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁸ Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
⁹ Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
¹⁰ Vector Institute for Artificial Intelligence, Toronto, ON, Canada.
¹¹ Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
¹² Data Science and Advanced Analytics, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
¹³ Department of Emergency Medicine, University of Ottawa, Ottawa, ON, Canada.
¹⁴ Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
¹⁵ School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.

^# Contributed equally.

PMID: 36933121
PMCID: PMC10024279
DOI: 10.1007/s43678-023-00480-8

Editorial

Teaching old tools new tricks-preparing emergency medicine for the impact of machine learning-based risk prediction models

Vinyas Harish et al. CJEM. 2023 May.

. 2023 May;25(5):365-369.

doi: 10.1007/s43678-023-00480-8. Epub 2023 Mar 18.

Authors

Vinyas Harish^#^{1

2

3

4}, Keerat Grewal^#^{5

6}, Muhammad Mamdani^{7

8

9

10

11

12}, Venkatesh Thiruganasambandamoorthy^{13

14

15}

Affiliations

¹ Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
² Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
³ Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
⁴ Vector Institute for Artificial Intelligence, Toronto, ON, Canada. v.harish@mail.utoronto.ca.
⁵ Division of Emergency Medicine, Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁶ Schwartz/Reisman Emergency Medicine Institute, Sinai Health, Toronto, ON, Canada.
⁷ Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁸ Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
⁹ Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
¹⁰ Vector Institute for Artificial Intelligence, Toronto, ON, Canada.
¹¹ Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
¹² Data Science and Advanced Analytics, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
¹³ Department of Emergency Medicine, University of Ottawa, Ottawa, ON, Canada.
¹⁴ Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
¹⁵ School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.

^# Contributed equally.

PMID: 36933121
PMCID: PMC10024279
DOI: 10.1007/s43678-023-00480-8

No abstract available

PubMed Disclaimer

Conflict of interest statement

The authors have no competing interests to declare.

References

1. Sax DR, Mark DG, Huang J, Sofrygin O, Rana JS, Collins SP, et al. Use of machine learning to develop a risk-stratification tool for emergency department patients with acute heart failure. Ann Emerg Med. 2021;77(2):237–248. doi: 10.1016/j.annemergmed.2020.09.436. - DOI - PubMed
1. White NJ, Contaifer D, Jr, Martin EJ, Newton JC, Mohammed BM, Bostic JL, et al. Early hemostatic responses to trauma identified with hierarchical clustering analysis. J Thromb Haemost. 2015;13(6):978–988. doi: 10.1111/jth.12919. - DOI - PMC - PubMed
1. Liu K, Li X, Zou CC, Huang H, Fu Y. Ambulance dispatch via deep reinforcement learning. In: Proceedings of the 28th international conference on advances in geographic information systems. New York: ACM; 2020. p. 123–6.
1. Wong A, Otles E, Donnelly JP, Krumm A, McCullough J, DeTroyer-Cooley O, et al. External validation of a widely implemented proprietary sepsis prediction model in hospitalized patients. JAMA Intern Med. 2021;181(8):1065–1070. doi: 10.1001/jamainternmed.2021.2626. - DOI - PMC - PubMed
1. Zech JR, Badgeley MA, Liu M, Costa AB, Titano JJ, Oermann EK. Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study. PLoS Med. 2018;15(11):e1002683. doi: 10.1371/journal.pmed.1002683. - DOI - PMC - PubMed

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Teaching old tools new tricks-preparing emergency medicine for the impact of machine learning-based risk prediction models

Affiliations

Teaching old tools new tricks-preparing emergency medicine for the impact of machine learning-based risk prediction models

Authors

Affiliations

Conflict of interest statement

References

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MeSH terms

Grants and funding

LinkOut - more resources

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