THE ROLE OF ARTIFICIAL INTELLIGENCE AND TELEMEDICINE IN THE MANAGEMENT OF CHRONIC DISEASES
DOI:
https://doi.org/10.11603/mie.1996-1960.2025.1-2.15991Keywords:
telemedicine, artificial intelligence, remote patient monitoring, chronic disease management, digital health, clinical decision supportAbstract
Abstract. Background. The rapid development of digital health technologies has significantly expanded the possibilities of telemedicine and artificial intelligence in modern healthcare systems.
Their integration creates new opportunities for remote medical care, continuous monitoring of patients, and improving the quality and accessibility of healthcare services, particularly in the management of chronic diseases.
Materials and Methods. The study was conducted using systematic and comparative analysis of contemporary scientific publications devoted to the application of telemedicine technologies and artificial intelligence in clinical practice. Methods of scientific generalization and interdisciplinary synthesis were applied to evaluate the prospects for integrating artificial intelligence tools into telemedicine systems for chronic disease management.
Results. The analysis demonstrates that the integration of telemedicine and artificial intelligence enables the development of advanced systems for remote monitoring, predictive modeling of disease progression, and clinical decision support. Machine learning algorithms allow the processing of large volumes of medical data, including clinical, laboratory, imaging, and biometric information, which improves diagnostic accuracy and facilitates personalized treatment planning. At the same time, the implementation of these technologies is associated with several challenges, including issues of data privacy and security, algorithm transparency, and the need to maintain trust between physicians and patients.
Conclusions. The integration of telemedicine and artificial intelligence forms a new paradigm of healthcare delivery focused on continuous monitoring, predictive analytics, and personalized management of chronic diseases. Further development of this field requires strengthening data governance, improving the reliability and interpretability of artificial intelligence systems, and developing regulatory and ethical frameworks for the effective use of digital technologies in healthcare.
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