Diabetes mellitus is a rapidly spreading chronic disease. IoT sensors enable real-time monitoring of glucose, heart rate, and other physiological parameters. This study compared CNN, RNN, and LSTM models, with LSTM achieving the highest accuracy (92.1%). Eliminating duplicate records improved model performance.
| Mualliflar | Kho'jaev, Otabek, Ruzmetova, Zilola |
|---|---|
| Jurnal | Techscience.uz - техника фанлари долзарб масалалри |
| Nashr sanasi | 2025-10-01 |
| Jild | 3 |
| Son | 7 |
| Betlar | 10-15 |
| Til | O‘zbek |
| DOI | 10.47390/ts-v3i7y2025n2 |
DOI: 10.47390/ts-v3i7y2025n2 · Maqolaning asl sahifasi
IoT, diabetes mellitus, neural networks, intelligent data processing, monitoring and prediction, artificial intelligence., IoT, qandli diabet, neyron tarmoqlar ,ma’lumotlarni intellektual qayta ishlash , monitoring va prognozlash, sun’iy intellekt.
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