Building artificial intelligence and machine learning models : a primer for emergency physicians
Ramlakhan, Shammi L and Saatchi, Reza and Sabir, Lisa and Ventour, Dale and Shobayo, Olamilekan and Hughes, Ruby and Singh, Yardesh (2022) Building artificial intelligence and machine learning models : a primer for emergency physicians. Emergency Medicine Journal, 39 (5). e1. ISSN 1472-0213 (https://doi.org/10.1136/emermed-2022-212379)
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Abstract
There has been a rise in the number of studies relating to the role of artificial intelligence (AI) in healthcare. Its potential in Emergency Medicine (EM) has been explored in recent years with operational, predictive, diagnostic and prognostic emergency department (ED) implementations being developed. For EM researchers building models de novo, collaborative working with data scientists is invaluable throughout the process. Synergism and understanding between domain (EM) and data experts increases the likelihood of realising a successful real-world model. Our linked manuscript provided a conceptual framework (including a glossary of AI terms) to support clinicians in interpreting AI research. The aim of this paper is to supplement that framework by exploring the key issues for clinicians and researchers to consider in the process of developing an AI model.
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Item type: Article ID code: 80067 Dates: DateEvent1 May 2022Published3 March 2022Published Online14 February 2022Accepted6 February 2022SubmittedSubjects: Technology > Manufactures Department: Faculty of Engineering > Design, Manufacture and Engineering Management > National Manufacturing Institute Scotland Depositing user: Pure Administrator Date deposited: 04 Apr 2022 11:51 Last modified: 06 Oct 2024 00:38 URI: https://strathprints.strath.ac.uk/id/eprint/80067