Artificial inteligence in chronic diseases: a scientometric analysis and its implications for clinical decision-making
Keywords:
Inteligencia Artificial; Aprendizaje Automático; Medicina de Precisión; Neoplasias; Bibliometría.Abstract
Introduction: Artificial intelligence has transformed modern clinical research, particularly in the
management of non-communicable chronic diseases. The massive and unstructured growth of current
scientific publications poses a critical challenge for the continuous updating and synthesis of scientific
evidence by medical professionals. Objective: To describe, from a scientometric perspective, the
evolution, intellectual structure, and trends of global scientific production regarding artificial intelligence
applied to non-communicable chronic diseases. Methods: A descriptive and cross-sectional study was
conducted using the Scopus database for the year 2024. Advanced data mining tools such as VOSviewer
and the R Bibliometrix package were used to process 9,181 documents, evaluating production indicators,
scientific impact, and international collaboration networks. Results: a sustained annual growth rate was
identified, with a notable h-index of 47 for the analyzed corpus. China and the United States have
consolidated their positions as the leading powers in production and citations. The thematic cluster
analysis revealed a marked predominance of deep learning applied to oncology, cardiology, and
high-precision diagnostic imaging, evidencing a transition toward personalized medicine. Conclusions:
Information saturation and technological complexity demand a profound shift in the educational paradigm.
The findings underscore the need to formally integrate data literacy into medical training. This approach
will strengthen specialists' competencies, facilitating clinical and surgical decision-making optimized
through artificial intelligence models, thus ensuring a more precise, efficient, and safe medical practice.
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Copyright (c) 2025 Eduardo Antonio Hernández-González, Annier Jesús Fajardo Quesada, Déborah Mitjans Hernández , Dariel Marín González, Sialy de las Mercedes Rivera López
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