Blood glucose prediction with deep neural networks using weighted decision level fusion

DÜDÜKÇÜ H. V., TAŞKIRAN M., YILDIRIM T.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, cilt.41, sa.3, ss.1208-1223, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 41 Sayı: 3
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.bbe.2021.08.007
  • Dergi Adı: BIOCYBERNETICS AND BIOMEDICAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, INSPEC
  • Sayfa Sayıları: ss.1208-1223
  • Anahtar Kelimeler: Blood glucose prediction, Long short term memory (LSTM), WaveNet, Gated recurrent units (GRU), Decision level fusion
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Background and Objective: Diabetes mellitus is a chronic disease that requires regular monitoring of blood glucose in the circulatory system. If the amount of glucose in the blood is not regulated constantly, this may have vital consequences for the individual. For this reason, there are many studies in the literature that perform blood glucose (BG) prediction.