Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice
9
Zitationen
7
Autoren
2025
Jahr
Abstract
To explore the attitudes of healthcare professionals and the public on applying ChatGPT in clinical practice. The successful application of ChatGPT in clinical practice depends on technical performance and critically on the attitudes and perceptions of non-healthcare and healthcare. This study has a qualitative design based on artificial intelligence. This study was divided into five steps: data collection, data cleaning, validation of relevance, sentiment analysis, and content analysis using the K-means algorithm. This study comprised 3130 comments amounting to 1,593,650 words. The dictionary method showed positive and negative emotions such as anger, disgust, fear, sadness, surprise, good, and happy emotions. Healthcare professionals prioritized ChatGPT's efficiency but raised ethical and accountability concerns, while the public valued its accessibility and emotional support but expressed worries about privacy and misinformation. Bridging these perspectives by improving reliability, safeguarding privacy, and clearly defining ChatGPT's role is essential for its practical and ethical integration into clinical practice.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.418 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.288 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.726 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 · 5.516 Zit.