Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating AI performance in infectious disease education: a comparative analysis of ChatGPT, Google Bard, Perplexity AI, Microsoft Copilot, and Meta AI
0
Zitationen
12
Autoren
2025
Jahr
Abstract
AI platforms offer potential in infectious disease education but demonstrate limitations in pharmacotherapy decision-making, particularly in antimicrobial selection and dosing accuracy. ChatGPT 3.5 performed best but lacked response stability, while Microsoft Copilot showed greater consistency but lacked nuanced therapeutic reasoning. Further research is needed to improve AI-driven decision support systems for medical education and clinical applications through clinical trials, evaluation of real-world patient data, and assessment of long-term stability.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.250 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.109 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.482 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.434 Zit.