Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Short Research Article: Evaluation of an artificial intelligence language model in psychiatric patient education
1
Zitationen
2
Autoren
2025
Jahr
Abstract
Background The incorporation of artificial intelligence (AI) and machine learning (ML) into medicine has enhanced clinical information processing. ChatGPT, an AI language model, has demonstrated proficiency in generating human‐like responses to complex medical queries. This study explores ChatGPT's potential to instruct parents on behavioral parent training (BPT) for managing attention‐deficit hyperactivity disorder (ADHD) in children. Methods ChatGPT was prompted with three parent‐focused questions regarding BPT for ADHD. An ADHD‐specialized psychiatrist reviewed the model's responses to assess clarity, accuracy, and clinical relevance. Results ChatGPT provided responses that were easy to understand and included actionable behavioral strategies. The answers referenced professional literature; however, some references were outdated. Limitations were noted in the specificity and depth of the information provided. Conclusion AI tools like ChatGPT show promise as supplementary resources in patient education and caregiver support. While helpful, current limitations—particularly in depth and reference accuracy—indicate a need for refinement to maximize their effectiveness in clinical communication and patient management contexts.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.700 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.605 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.133 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.873 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.