Bibliometric Analysis of Artificial Intelligence Research in the Healthcare

Authors : Emrah Atılgan

Pages : 13-23

View : 80 | Download : 84

Publication Date : 2024-04-28

Article Type : Research Paper

Abstract :Artificial intelligence (AI) has a revolutionary impact on the healthcare sector, offering innovative solutions that can lead to significant transformation. Utilizing capabilities such as machine learning, virtual health assistants, natural language processing, robotics, and computer vision, AI technologies enable healthcare professionals to analyze extensive medical data rapidly and accurately. Algorithms driven by AI contribute to early disease diagnosis, risk assessment, and the creation of personalized treatment plans, enhancing the delivery of beneficial solutions to patients and providing more cost-effective healthcare services. In addition to clinical applications, AI shapes healthcare management through patient management, resource allocation, and predictive analytics tools. It is known that AI-supported solutions optimize healthcare services by reducing costs and improving the quality of care. The aim of this article is to elucidate the quantitative and qualitative characteristics of AI in healthcare. Methodologically, a comprehensive bibliometric analysis of academic publications related to AI in healthcare was conducted, presenting information on research and knowledge dissemination at the intersection of this critical technology and the healthcare sector\'s development. Between 1992 and 2023, 1966 studies indexed in Web of Science, contributed by 7460 authors, were examined. The United States emerged as the leading country in terms of the highest number of studies and citations, with IEEE Access being the leading journal. The most prolific author in this field was Yang Zang, while Diana J. Cook was the most cited author, with the article titled “Ambient intelligence: Technologies, applications, and opportunities,” authored by Diana J. Cook and colleagues, being the most cited article. The most notable topics in this field were “artificial intelligence,” “deep learning,” “machine learning,” and “COVID-19.” The results indicate a significant increase in the use of AI in the healthcare sector in recent years, with this trend expected to continue growing in the coming years. Understanding current trends, major contributors, and evolving aspects of interest provides valuable practical insights for stakeholders aiming to fully leverage the potential of AI in healthcare. Considering that AI is rapidly developing, it can be predicted that its role in health will become more important by contributing to more efficient healthcare systems such as more reliable patient outcomes and increased accessibility. Possible contributions of the obtained results for studies and applications in this field, aspects that need improvement and limitations are discussed in the discussion section.
Keywords : Yapay Zeka, Sağlık, Derin Öğrenme, Makine Öğrenmesi