This article addresses the development of a remote cardiovascular disease monitoring system integrated with Natural Language Processing (NLP) technologies. Based on a systematic literature review and comparative analysis of existing approaches, a conceptual model of a universal monitoring system is proposed. The system employs a BERT-based NLP model to automatically analyze patients' verbal complaints and processes them together with clinical indicators from IoT sensors. The proposed architecture enables a reduction in hospital visits and optimization of medical staff workload in monitoring hypertension, arrhythmia, and heart failure. Literature analysis indicates that integrating an NLP component into a monitoring system can increase anomaly detection efficiency by an average of 15-25%.
| Mualliflar | Ergasheva, Okhuna, Rakhimova, Mehrbonu |
|---|---|
| Jurnal | Techscience.uz - техника фанлари долзарб масалалри |
| Nashr sanasi | 2026-03-25 |
| Jild | 4 |
| Son | 3 |
| Betlar | 12-18 |
| Til | O‘zbek |
| DOI | 10.47390/ts-v4i3y2026n02 |
DOI: 10.47390/ts-v4i3y2026n02 · Maqolaning asl sahifasi
remote monitoring, natural language processing, NLP, cardiovascular disease, BERT, artificial intelligence, IoT, digital medicine, telemedicine., masofadan monitoring, tabiiy tilni qayta ishlash, NLP, yurak-qon tomir kasalliklari, BERT, sun'iy intellekt, IoT, raqamli tibbiyot, telemeditsina
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