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

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

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, vol.41, no.3, pp.1208-1223, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 41 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.1016/j.bbe.2021.08.007
  • Journal Name: BIOCYBERNETICS AND BIOMEDICAL ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, INSPEC
  • Page Numbers: pp.1208-1223
  • Keywords: Blood glucose prediction, Long short term memory (LSTM), WaveNet, Gated recurrent units (GRU), Decision level fusion
  • Yıldız Technical University Affiliated: Yes

Abstract

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.