Introduction Artificial intelligence (AI)-powered tools are increasingly integrated into healthcare. The purpose of the present study was to compare fracture management plans generated by clinicians to those obtained from ChatGPT (OpenAI, San Francisco, CA) and Google Gemini (Google, Inc., Mountain View, CA). Methodology A retrospective comparative analysis was conducted. The study included 70 cases of isolated injuries treated at the authors' institution fracture clinic. Complex, open fractures and non-specific diagnoses were excluded. All relevant clinical details were introduced into ChatGPT and Google Gemini. The AI-generated management plans were compared with actual documented plans obtained from the clinical records. The study focused on treatment recommendations and follow-up strategies. Results In terms of agreement with actual treatment plans, Google Gemini matched in only 13 cases (19%), with disagreements in the remainder of cases due to overgeneralisation, inadequate treatment, and ambiguity. In contrast, ChatGPT matched actual plans in 24 cases (34%), with overgeneralisation being the principal cause for disagreement. The differences between AI-powered tools and actual clinician-led plans were statistically significant (p < 0.001). Conclusion Both AI-powered tools demonstrated significant disagreement with actual clinical management plans. While ChatGPT showed closer alignment to human expertise, particularly in treatment recommendations, both AI engines still lacked the clinical precision required for accurate fracture management. These findings highlight the current limitations of ordinary AI-powered tools and negate their ability to replace a clinician-led fracture clinic appointment.
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http://dx.doi.org/10.7759/cureus.75440 | DOI Listing |
J Pers Med
January 2025
Bruyère Research Institute, University of Ottawa, Ottawa, ON K1N 5C7, Canada.
: Artificial intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy, treatment, and patient monitoring, benefiting older adults by offering personalized care plans. AI-powered tools help manage chronic conditions and maintain independence, making them a valuable asset in addressing aging challenges. : The objectives are as follows: 1.
View Article and Find Full Text PDFJ Pers Med
January 2025
Sezione di Chirurgia Protesica ad Indirizzo Robotico-Unità di Traumatologia dello Sport, Ortopedia e Traumatologia, Fondazione Poliambulanza, 25124 Brescia, Italy.
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View Article and Find Full Text PDFMed Sci (Basel)
January 2025
Faculty of Education, Tel-Hai Academic College, Upper Galilee 2208, Israel.
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View Article and Find Full Text PDFBiochim Biophys Acta Mol Basis Dis
January 2025
AIBioMed Research Group, Taipei Medical University, Taipei 110, Taiwan; In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan. Electronic address:
The convergence of artificial intelligence (AI) and genomics is redefining cancer drug discovery by facilitating the development of personalized and effective therapies. This review examines the transformative role of AI technologies, including deep learning and advanced data analytics, in accelerating key stages of the drug discovery process: target identification, drug design, clinical trial optimization, and drug response prediction. Cutting-edge tools such as DrugnomeAI and PandaOmics have made substantial contributions to therapeutic target identification, while AI's predictive capabilities are driving personalized treatment strategies.
View Article and Find Full Text PDFJ Expo Sci Environ Epidemiol
January 2025
Department of Veterinary Physiology & Pharmacology, Texas A&M University, College Station, TX, USA.
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