Academic Journal
Evaluating artificial intelligence in decision-making for surgical treatment of benign breast conditions
| Τίτλος: | Evaluating artificial intelligence in decision-making for surgical treatment of benign breast conditions |
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| Συγγραφείς: | De Pellegrin, Laura, Weinzierl, Andrea, Kappos, Elisabeth A, Lindenblatt, Nicole, Zucal, Isabel, Harder, Yves |
| Συνεισφορές: | University of Zurich, Harder, Yves |
| Πηγή: | Journal of plastic, reconstructive & aesthetic surgery, vol. 105, pp. 189-195 |
| Στοιχεία εκδότη: | Elsevier BV, 2025. |
| Έτος έκδοσης: | 2025 |
| Θεματικοί όροι: | Artificial intelligence, Breast pathologies, 610 Medicine & health, Clinical evaluation, 10266 Clinic for Reconstructive Surgery, Humans, Artificial Intelligence, Female, Breast Diseases/surgery, Clinical Decision-Making/methods, Adult, Middle Aged, Decision-making, Therapeutic planning, 2746 Surgery |
| Περιγραφή: | Introduction Determining the ideal surgical strategy for breast pathologies can sometimes be challenging, in particular if personalized solutions are required. Moreover, acquiring the necessary expertise takes years. Artificial intelligence (AI) may help streamline decision-making and improve treatment approaches. This study assessed the potential role of AI in therapeutic planning for common breast pathologies.Methods Five clinical cases representing common breast pathologies were presented to ChatGPT-4o, an advanced AI model. Its responses were evaluated by 16 board-certified plastic surgeons and 9 residents for accuracy, relevance, and completeness using a Likert scale. Readability scores were also assessed by considering word length, syllable count, and sentence complexity.Results AI-generated responses were found to be medically accurate, well-structured, and comprehensible. However, they lacked depth in surgical planning and risk assessment. The readability scores were Flesch Reading Ease (27.9), Flesch-Kincaid Grade Level (14.3), and Coleman-Liau Index (15.0), indicating a relatively high reading level.Conclusion ChatGPT-4o can assist in analyzing breast pathologies; however, it does not account for individual patient factors and surgical nuances. Although ChatGPT-4o is not yet suitable for independent decision-making, further refinement, training, and expert validation could enhance the AI's role in future clinical applications. |
| Τύπος εγγράφου: | Article Other literature type |
| Περιγραφή αρχείου: | application/pdf; ZORA_278331.pdf - application/pdf |
| Γλώσσα: | English |
| ISSN: | 1748-6815 |
| DOI: | 10.1016/j.bjps.2025.03.057 |
| DOI: | 10.48620/87917 |
| DOI: | 10.5167/uzh-278331 |
| Σύνδεσμος πρόσβασης: | https://pubmed.ncbi.nlm.nih.gov/40305890 http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_61B7F127B36D0 https://serval.unil.ch/resource/serval:BIB_61B7F127B36D.P001/REF.pdf https://serval.unil.ch/notice/serval:BIB_61B7F127B36D |
| Rights: | CC BY |
| Αριθμός Καταχώρησης: | edsair.doi.dedup.....8e73d7f6c03fba63bf09a8d91c056a61 |
| Βάση Δεδομένων: | OpenAIRE |
| ISSN: | 17486815 |
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| DOI: | 10.1016/j.bjps.2025.03.057 |