Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating the Role of ChatGPT in Health Information Provision: Capabilities, Limitations, and Ethical Implications
1
Zitationen
2
Autoren
2025
Jahr
Abstract
This study provides a critical analysis of ChatGPT's strengths and weaknesses as a resource for delivering health-related information, emphasizing its potential for both general advice and tailored health guidance. Through a systematic review and expert analysis, the study highlights ChatGPT's ability to deliver immediate and accessible information on a wide range of health topics, including nutrition and chronic disease management. While its conversational interface and capacity for personalization make it a valuable resource for users seeking initial advice, significant limitations are evident in its handling of complex and nuanced health scenarios. These shortcomings are primarily attributed to gaps in its training, including outdated data and potential incorporation of unverified sources. The findings emphasize the importance of recognizing ChatGPT as a supplementary tool rather than a replacement for professional healthcare consultation. Ensuring user safety requires ongoing updates to its training datasets, integration of the latest scientific evidence, and the establishment of clear guidelines for its application in healthcare settings. The study underscores the critical role of qualified professionals in verifying and contextualizing AI-generated advice, particularly in complex or high-risk cases. Future research and development are essential to enhance ChatGPT's reliability, accuracy, and effectiveness, ensuring its optimal contribution to health information dissemination while maintaining the highest standards of safety and ethics.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.239 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.428 Zit.