Academic Journal
Agreement Between AI Language Models and BOOM Chondrosarcoma Consensus Statements: A Comparative Study.
| Τίτλος: | Agreement Between AI Language Models and BOOM Chondrosarcoma Consensus Statements: A Comparative Study. |
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| Συγγραφείς: | Dünki A, Polat Ö |
| Πηγή: | Acta orthopaedica Belgica [Acta Orthop Belg] 2026 Apr 20; Vol. 92 (1). Date of Electronic Publication: 2026 Apr 20. |
| Τύπος έκδοσης: | Journal Article; Comparative Study |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Acta Medica Belgica Country of Publication: Belgium NLM ID: 2985165R Publication Model: Electronic Cited Medium: Internet ISSN: 0001-6462 (Print) Linking ISSN: 00016462 NLM ISO Abbreviation: Acta Orthop Belg Subsets: MEDLINE |
| Imprint Name(s): | Publication: Bruxelles : Acta Medica Belgica Original Publication: Bruxelles. |
| Ιατρικοί όροι (MeSH): | Chondrosarcoma*/therapy , Bone Neoplasms*/therapy , Consensus Statements as Topic* , Artificial Intelligence* , Orthopedics*, Humans ; Consensus ; Large Language Models |
| Περίληψη: | Artificial intelligence (AI) is an exciting development makes life easier and solves many problems in daily life. The Birmingham Orthopaedic Oncology Meeting (BOOM) met in January 2024 with 309 participants from 53 countries to discuss the optimal consensus for chondrosarcomas on 21 questions. The aim of this study was to investigate how reliable the expert statements from the BOOM were compared to ChatGPT-4 and DeepseekR1. 21 questions and consensus statements in the section on chondrosarcomas in the BOOM were extracted. The answers were classified according to the level of evidence and consensus status, taking into account the consensus strength category determined in the meeting. Each statement were written separately for the ChatGPT-4 and DeepseekR1. Consensus questions and answers were written for the AI modules and they were asked to interpret these expressions as ''strongly disagree, disagree, undecided, agree or strongly agree''. BOOM participants reached a strong consensus on 19 questions. The number of people who accepted the proposition for 1 question was 52% and no consensus was reached. ChatGPT-4 and DeepseekR1 responded ''disagree'' for a same question. The level of evidence for that question was ''low to moderate'' and a strong consensus was reached. A significant relationship was found between the responses of ChatGPT-4 and DeepseekR1. ChatGPT-4 and Deepseek expressed more positive opinions in the answers with high levels of evidence, while BOOM participants were able to make stronger consensus decisions by combining their clinical observations with literature knowledge, regardless of level of evidence. |
| Entry Date(s): | Date Created: 20260421 Date Completed: 20260715 Latest Revision: 20260715 |
| Update Code: | 20260715 |
| DOI: | 10.52628/92.1.14560 |
| PMID: | 42012044 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 0001-6462 |
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| DOI: | 10.52628/92.1.14560 |