Comprehensive Telemedicine for Complex Geriatric Patients: An AI-Based Care Model for the Early Detection of Gastrointestinal and Nephrological Decompensations

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Artificial intelligence (AI)-enhanced telemedicine is emerging as a promising approach for managing complex geriatric patients, a group at high risk for decompensations. However, the intellectual structure and evolutionary trends of this specific research area remain unclear. To conduct a bibliometric analysis to map the scientific landscape on the application of AI and telemedicine for the early detection of gastrointestinal and nephrological decompensations in complex geriatric patients. A systematic bibliometric analysis was conducted using the Scopus database. The search, performed on [2024], identified 428 documents, of which 87 met the inclusion criteria. The analysis included publication trends, co-word analysis using VOSviewer, citation analysis, and thematic synthesis. Scientific output showed exponential growth from 2015 onwards. Co-occurrence analysis revealed three main thematic clusters: 1) The Geriatric-Technological Interface (patient needs), 2) The AI-Data Core (methods), and 3) The Clinical Application Domain (specific conditions). A significant research gap was identified in gastrointestinal decompensations compared to nephrological and cardiometabolic conditions. This bibliometric study reveals a vibrant yet maturing research field. The field must evolve towards developing AI systems capable of handling polypathology and subjective symptoms, requiring closer collaboration between geriatricians and data scientists to realize its full potential.