Application of Artificial Intelligence in Geriatric Care: Bibliometric Analysis

No prior work had resolved the full scope of technological integration within elderly support systems. That uncertainty drove a need to map the evolving landscape of digital health tools. Prior research has shown that automated systems offer potential benefits for patient well-being. However, the specific trajectory of these innovations remained poorly defined in existing literature. This gap motivated a comprehensive review of scholarly output spanning over two decades. Scholars have noted that nursing environments face increasing pressures from demographic shifts. Yet, the connectivity between global research groups has not been systematically evaluated. That lack of clarity hindered the ability to identify emerging priorities for clinical practice.

The aim of this study is to evaluate the current research hotspots and collaborative networks in the application of artificial intelligence for elderly support. This investigation seeks to clarify the developmental status of this field over the last twenty-three years. The authors address the need to identify primary contributors and their professional relationships. By synthesizing existing data, the work provides a clear picture of how technology is being integrated into nursing practices. This effort is motivated by the rapid growth of publications in recent years. No prior work had resolved the specific thematic clusters currently driving innovation in this sector. That uncertainty drove the researchers to perform a systematic mapping of the available literature. The study provides essential information for scholars seeking to understand the current state of this evolving discipline.

The review approach involved a systematic search of the Web of Science Core Collection database. Investigators gathered all relevant documents published from the initial record through August 2022. Quantitative techniques helped summarize external publication attributes using specialized software platforms. The team modeled thematic clusters to categorize the collected literature into distinct research domains. Collaborative networks were mapped to visualize the connections between various global contributors. This design focused on extracting patterns from 230 total publications. The authors processed data from 499 institutions across 39 different countries. This methodology ensured a comprehensive overview of the field's historical and current trajectory.

Key findings from the literature show that publication volume surged significantly between 2014 and 2022. During this period, 209 of the 230 total publications were released, representing 90.87% of the entire dataset. The United States emerged as the leading contributor in terms of total publication output. The International Journal of Social Robotics was identified as the most frequent venue for these studies. Researchers organized 1,216 authors into five primary clusters based on their specific thematic contributions. Four major thematic clusters included Alzheimer disease, aged care, acceptance, and disease surveillance. Recent hotspots identified by the study include machine learning, deep learning, and rehabilitation techniques. The data indicates that while output is growing, institutional and regional cooperation remains relatively limited.

The authors propose that international partnerships remain currently constrained across various academic institutions. Strengthening these cross-border links might accelerate progress within this specialized medical domain. Future investigations should prioritize expanding collaborative networks to enhance global knowledge sharing. The researchers suggest that current trends indicate a rapid expansion of digital health applications. This synthesis highlights that specific disease management remains a primary focus for many investigators. The findings imply that nursing care models will likely evolve alongside these technological advancements. The authors recommend that stakeholders focus on bridging existing gaps in institutional cooperation. This review offers a roadmap for understanding the current state of this rapidly growing field.