KEY PUBLICATIONS OF 2021–2025 ON ARTIFICIAL INTELLIGENCE METHODS IN THE MANUFACTURING AND DIAGNOSTICS OF MEDICAL DEVICES FOR GLYCEMIC MONITORING: A THEMATIC ANALYTICAL REVIEW

Abstract

Artificial intelligence is increasingly being applied in the manufacturing and diagnostics of medical devices, including systems for glycemic monitoring, where accuracy, reliability, and quality control are critically important. The aim of this study was to systematize key publications from 2021 to 2025 on the use of artificial intelligence in the manufacturing and diagnostics of glycemic-monitoring medical devices and to identify the main technological directions, practical opportunities, and implementation limitations. The review was based on 68 publications selected from Scopus, Web of Science, PubMed, IEE Xplore, and regulatory sources. The analysis identified five principal thematic areas: computer vision and defect detection, predictive quality management and anomaly detection, artificial intelligence in continuous glucose monitoring and biosensor systems, foundational computational architectures, and regulatory standards. The results show a clear shift from experimental studies to implementation-oriented and regulation-aware solutions. Overall, artificial intelligence demonstrates strong potential for improving production quality assurance, biosensor calibration, and medical device lifecycle support.