Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy
12
Zitationen
13
Autoren
2025
Jahr
Abstract
Overall, LLMs show promise as a tool for patient education in prostate cancer radiotherapy. While improvements are needed in terms of accuracy and readability, positive feedback from clinicians and patients suggests that LLMs can enhance patient understanding and engagement. Further research is essential to fully realize the potential of artificial intelligence in patient education.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.393 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.259 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.688 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.502 Zit.