Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence Performs Well for Patient-Level Education of Benign Anorectal Conditions
2
Zitationen
5
Autoren
2025
Jahr
Abstract
= 0.001). It performed weakest within the mEQIP Identification domain. It primarily lost points for recommending non-evidence-based treatments, lack of citations and visual aids, and generating broken source links.DiscussionChatGPT can provide accurate, reliable information at patient understanding level and is comparable to other validated online information for benign anorectal pathologies. It could improve on mEQIP performance by improving source documentation and visual aid capability, but it remains a promising patient resource with an intuitive user interface.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.560 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.451 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.948 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.797 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.