# Mapping How Artificial Intelligence Blends with Healthcare: Insights from a Bibliometric Analysis
## 1 Introduction  
Undoubtedly, the potential of AI has raised great expectations in industries such as healthcare. This is because the challenges faced by humanity in the field of health are diverse and of varying nature. The case of COVID-19 alone has underscored how vulnerable humanity is to such challenges, where failing to address them results in significant costs, including the loss of lives. Therefore, AI emerges as a crucial resource in humanity's endeavor to confront these challenges and improve living conditions. The integration of AI in the context of medical research has not only taken place in the last four years, during which we have witnessed a significant surge in interest but has actually been ongoing for decades. A prime example of this is the research project conducted by [PERSON] et al. [1]. During this early phase, these scholars focused on issues related to interactive graphics within computer-mediated medical seminars. Similarly, a few years later, [PERSON] [2] evaluated the importance of the interaction of AI in another field, specifically psychotherapy, examining the evolving perspective around the psychotherapeutic interaction between humans and computers. The last term is also the prevailing one in the relevant literature, evolving with different definitions over the years. [PERSON] et al. [3], [PERSON] et al. [4], [PERSON] and [PERSON] [5], and [PERSON] et al. [6] introduced the term \"Man-Machine Interaction\" in the 1980s. [PERSON] and [PERSON] [7] in the late 1990s distinguished between \"Human-Machine Interactions\" and \"Human-Robot Interactions\". More recently, several scholars have adopted the term \"human-artificial intelligence interaction\", including [PERSON] et al. [8], [PERSON] et al. [9], [PERSON] et al. [10], [PERSON] et al. [11], and [PERSON] et al. [12]. The diversity of the conceptual definition, however, is not accidental. Given the multidimensionality of medical issues, AI has all of the elements needed to address long-standing and entrenched challenges in various medical disciplines. Special emphasis has clearly been given to the treatment of various forms of cancer and oncology [13; 14; 15], geriatrics [16; 17], cardiology [18], and even dentistry [19]. The specific aim of this research is to analytically describe and critically assess the scope and depth of AI's utilization in different medical fields, identifying technological advancements as well as areas needing further exploration. For this purpose, this study introduces a novel bibliometric approach by comprehensively tracing the evolution and integration of AI within these sectors, highlighting key trends and shifts not previously synthesized in the literature. Many researchers have attempted to review the integration of AI in healthcare [20; 21]; however, these reviews have not comprehensively covered the entire period from the initial stages of AI, nor have they provided detailed information per medical department. Our research fills this critical gap by offering new insights into AI's role and its developmental trajectory in healthcare, and pinpointing specific applications and impacts across various medical specialties. Hence, this research seeks to address the following questions:  
1. What are the most influential countries, institutions, sources, and authors in the field of AI interaction with healthcare? 2. What are the main thematic areas of research in AI interaction with healthcare? 3. Which medical departments have integrated AI according to each thematic area of research? The structure of the paper is as follows: We begin by detailing our research methodology. We then proceed to the analysis phase, starting with an explanation of our bibliometric and cluster-based content analysis. Following this, we identify the thematic subjects of the relevant literature. This leads us into the discussion section, where we elaborate on the advancements made using AI over the years in various medical areas, organized by thematic area.