THE ROLE OF TELEMEDICAL SYSTEMS AND ARTIFICIAL INTELLIGENCE IN POSTOPERATIVE MONITORING OF NEUROSURGICAL PATIENTS: A SYSTEMATIC REVIEW
Abstract
Introduction. Postoperative observation of patients with brain pathologies, particularly benign skull base tumors, presents a complex clinical and logistical challenge. Traditional face-to-face monitoring methods are often associated with risks for debilitated patients and significant financial costs.
Objective. To conduct a systematic analysis of the effectiveness and economic feasibility of implementing telemedicine technologies and Artificial Intelligence (AI) algorithms in the rehabilitation process of neurosurgical patients.
Materials and Methods. A systematic literature review was performed using PubMed, Scopus, and eLibrary databases for the period 2018–2024. Inclusion criteria were the presence of a control group, quantitative outcome assessment, and a focus on neuro-oncology.
Results. Fifteen key studies were analyzed. It was established that telemedicine consultations reduce the economic burden on the patient by an average of 40-60% without compromising clinical outcomes (readmission rates are comparable to in-person visits). AI algorithms demonstrate a sensitivity of over 90% in the early detection of recurrence based on MRI data.
Conclusion. The digital transformation of neurosurgical monitoring is a necessary step to improve the accessibility of care and treatment personalization.
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References
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