- Title
- Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey
- Creator
- Cobianchi, Lorenzo; Piccolo, Daniele; Dal Mas, Francesca; Agnoletti, Vanni; Ansaloni, Luca; Balch, Jeremy; Biffl, Walter; Butturini, Giovanni; Catena, Fausto; Coccolini, Federico; Denicolai, Stefano; De Simone, Belinda; Frigerio, Isabella; Fugazzola, Paola; Marseglia, Gianluigi; Marseglia, Giuseppe Roberto; Martellucci, Jacopo; Modenese, Mirko; Previtali, Pietro; Ruta, Federico; Enninghorst, Natalie; Amico, Francesco; Venturi, Alessandro; Kaafarani, HM; Loftus, TJ; Abbott, KL; Abdelmalik, A; Abebe, NS; Abu-Zidan, F; Adam, YAY; Adamou, H; Adamovich, DM; Agresta, F; Agrusa, A; Akin, E; Alessiani, M; Alexandrino, H; Ali, SM; Mihai, VA; Almeida, PM; Al-Shehari, MM; Altomare, M; Ammendola, M; Andreuccetti, J; Anestiadou, E; Angelos, P; Annicchiarico, A; Antonelli, A; Aparicio-Sanchez, D; Ardito, A; Argenio, G; Arvieux, CC; Askevold, IH; Atanasov, BT; Augustin, G; Awad, SS; Bacchiocchi, G; Bagnoli, C; Bahouth, H; Baili, E; Bains, L; Baiocchi, GL; Bala, M; Balagué, C; Balalis, D; Baldini, E; Baraket, O; Baral, S; Barone, M; Barranquero, AG; Barreras, JA; Bass, GA; Bayhan, Z; Bellanova, G; Ben-Ishay, O; Bert, F; Bianchi, V; Biancuzzi, H; Bidoli, C; Radulescu, RB; Bignell, MB; Biloslavo, A; Bini, R; Bissacco, D; Boati, P; Boddaert, G; Bogdanic, B; Bombardini, C; Bonavina, L; Bonomo, L; Bottari, A; Bouliaris, K; Brachini, G; Brillantino, A; Brisinda, G; Bulanauca, MM; Buonomo, LA; Burcharth, J; Buscemi, S; Calabretto, F; Calini, G
- Relation
- World Journal of Emergency Surgery Vol. 18, Issue 1, no. 1
- Publisher Link
- http://dx.doi.org/10.1186/s13017-022-00467-3
- Publisher
- BioMed Central (BMC)
- Resource Type
- journal article
- Date
- 2023
- Description
- 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.
- Subject
- artificial intelligence; clinical decision-making; decision aids; trauma and emergency surgery; survey
- Identifier
- http://hdl.handle.net/1959.13/1494215
- Identifier
- uon:53750
- Identifier
- ISSN:1749-7922
- Rights
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
- Language
- eng
- Full Text
- Reviewed
- Hits: 8188
- Visitors: 8172
- Downloads: 42
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT02 | Publisher version (open access) | 2 MB | Adobe Acrobat PDF | View Details Download |