Background: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive trauma and emergency contexts are often challenging. The study aims to investigate trauma and emergency surgeons’ knowledge and perception of using AI-based tools in clinical decision-making processes. Methods: An online survey grounded on literature regarding AI-enabled surgical decision-making aids was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was advertised to 917 WSES members through the society’s website and Twitter profile. Results: 650 surgeons from 71 countries in five continents participated in the survey. Results depict the presence of technology enthusiasts and skeptics and surgeons’ preference toward more classical decision-making aids like clinical guidelines, traditional training, and the support of their multidisciplinary colleagues. A lack of knowledge about several AI-related aspects emerges and is associated with mistrust. Discussion: The trauma and emergency surgical community is divided into those who firmly believe in the potential of AI and those who do not understand or trust AI-enabled surgical decision-making aids. Academic societies and surgical training programs should promote a foundational, working knowledge of clinical AI.

Cobianchi, L., Piccolo, D., Dal Mas, F., Agnoletti, V., Ansaloni, L., Balch, J., et al. (2023). Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey. WORLD JOURNAL OF EMERGENCY SURGERY, 18 [10.1186/s13017-022-00467-3].

Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey

Ansaloni L.;Ceresoli M.
Membro del Collaboration Group
;
Nespoli L.;
2023

Abstract

Background: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive trauma and emergency contexts are often challenging. The study aims to investigate trauma and emergency surgeons’ knowledge and perception of using AI-based tools in clinical decision-making processes. Methods: An online survey grounded on literature regarding AI-enabled surgical decision-making aids was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was advertised to 917 WSES members through the society’s website and Twitter profile. Results: 650 surgeons from 71 countries in five continents participated in the survey. Results depict the presence of technology enthusiasts and skeptics and surgeons’ preference toward more classical decision-making aids like clinical guidelines, traditional training, and the support of their multidisciplinary colleagues. A lack of knowledge about several AI-related aspects emerges and is associated with mistrust. Discussion: The trauma and emergency surgical community is divided into those who firmly believe in the potential of AI and those who do not understand or trust AI-enabled surgical decision-making aids. Academic societies and surgical training programs should promote a foundational, working knowledge of clinical AI.
Articolo in rivista - Articolo scientifico
Artificial intelligence; Clinical decision-making; Decision aids; Survey; Trauma and emergency surgery;
English
3-gen-2023
2023
18
1
open
Cobianchi, L., Piccolo, D., Dal Mas, F., Agnoletti, V., Ansaloni, L., Balch, J., et al. (2023). Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey. WORLD JOURNAL OF EMERGENCY SURGERY, 18 [10.1186/s13017-022-00467-3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/410937
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