Generative Artificial Intelligence in Healthcare: A Bibliometric Analysis and Review of Potential Applications and Challenges

The remarkable progress of artificial intelligence (AI) in recent years has significantly extended its application possibilities within the healthcare domain. AI has become more accessible to a wider range of healthcare personnel and service users, in particular due to the proliferation of Generative AI (GenAI). This study presents a bibliometric analysis of GenAI in healthcare. By analysing the Scopus database academic literature, our study explores the knowledge structure, emerging trends, and challenges of GenAI in healthcare. The results showed that GenAI is increasingly being adoption in developed countries, with major US institutions leading the way, and a large number of papers are being published on the topic in top-level academic venues. Our findings also show that there is a focus on particular areas of healthcare, with medical education and clinical decision-making showing active research, while areas such as emergency medicine remain poorly explored. Our results also show that while there is a focus on the benefits of GenAI for the healthcare industry, its limitations need to be acknowledged and addressed to facilitate its integration in clinical settings. The findings of this study can serve as a foundation for understanding the field, allowing academics, healthcare practitioners, educators, and policymakers to better understand the current focus within GenAI for healthcare, as well as highlighting potential application areas and challenges around accuracy, privacy, and ethics that must be taken into account when developing healthcare-focused GenAI applications.