Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
3Ps for ChatGPT: Best Practices for Generative AI Discharge Instructions (Preprint)
0
Zitationen
5
Autoren
2024
Jahr
Abstract
<sec> <title>UNSTRUCTURED</title> Patients may leave the emergency room unsatisfied since so much of their care occurs away from their view. Additionally, generic discharge instructions further contribute to this dissatisfaction, lacking detail on the care provided and specific home guidance and precautions. The patients, their families, or care teams may then be left with lingering questions and potential adverse outcomes due to misinterpretation. Research has shown a positive correlation between patient satisfaction and their assessment of the quality of discharge instructions, but providers in a fast-paced emergency room are limited by time. The expansion and availability of AI technologies in recent years offer a potential solution. This article details a multi-step approach to interact with AI-powered language learning models, specifically ChatGPT3.5, to compose targeted, specific, and clear discharge instructions. We propose that strategic implementation of these technologies can improve both efficiency and promote patient-centered care. </sec>
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.578 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.470 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.984 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.814 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.