PERSONALIZED BLOOD GLUCOSE FORECASTING FROM CGM DATA USING AN INCREMENTALLY RETRAINED LSTM

被引:0
|
作者
Shen, Y. [1 ]
Kleinberg, S. [1 ]
机构
[1] Stevens Inst Technol, Comp Sci, Hoboken, NJ USA
关键词
D O I
暂无
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
452
引用
收藏
页码:A140 / A140
页数:1
相关论文
共 50 条
  • [31] Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent Neural Networks
    Armandpour, Mohammadreza
    Kidd, Brian
    Du, Yu
    Huang, Jianhua Z.
    [J]. 2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2021,
  • [32] Enhancing Grammatical Evolution Through Data Augmentation: Application to Blood Glucose Forecasting
    Manuel Velasco, Jose
    Garnica, Oscar
    Contador, Sergio
    Manuel Colmenar, Jose
    Maqueda, Esther
    Botella, Marta
    Lanchares, Juan
    Ignacio Hidalgo, J.
    [J]. APPLICATIONS OF EVOLUTIONARY COMPUTATION, EVOAPPLICATIONS 2017, PT I, 2017, 10199 : 142 - 157
  • [33] Touch-Based Fingertip Blood-Free Reliable Glucose Monitoring: Personalized Data Processing for Predicting Blood Glucose Concentrations
    Sempionatto, Juliane R.
    Moon, Jong-Min
    Wang, Joseph
    [J]. ACS SENSORS, 2021, 6 (05) : 1875 - 1883
  • [34] Randomized comparison of self-monitored blood glucose (BGM) versus continuous glucose monitoring (CGM) data to optimize glucose control in type 2 diabetes
    Bergenstal, Richard M.
    Mullen, Deborah M.
    Strock, Ellie
    Johnson, Mary L.
    Xi, Min X.
    [J]. JOURNAL OF DIABETES AND ITS COMPLICATIONS, 2022, 36 (03)
  • [35] Incorporating Glucose Variability into Glucose Forecasting Accuracy Assessment Using the New Glucose Variability Impact Index and the Prediction Consistency Index: An LSTM Case Example
    Mosquera-Lopez, Clara
    Jacobs, Peter G.
    [J]. JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, 2022, 16 (01): : 7 - 18
  • [36] A Multi Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model
    Zaheer, Shahzad
    Anjum, Nadeem
    Hussain, Saddam
    Algarni, Abeer D. D.
    Iqbal, Jawaid
    Bourouis, Sami
    Ullah, Syed Sajid
    [J]. MATHEMATICS, 2023, 11 (03)
  • [37] Analysis and forecasting of Time-Series data using S-ARIMA, CNN and LSTM
    Dwivedi, Subhash Arun
    Attry, Amit
    Parekh, Darshan
    Singla, Kanika
    [J]. 2021 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION, AND INTELLIGENT SYSTEMS (ICCCIS), 2021, : 131 - 136
  • [38] Use of Continuous Glucose Monitoring (CGM) with Personalized Instructions Provides Glycemic Benefit to Patients Using Multiple Daily Insulin Injections (MDI)
    Price, David A.
    Gerety, Gregg
    Blevins, Thomas C.
    Casal, Eileen
    [J]. DIABETES, 2015, 64 : A195 - A195
  • [39] A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data
    Arslan, Serdar
    [J]. PeerJ Computer Science, 2022, 8
  • [40] A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data
    Arslan, Serdar
    [J]. PEERJ COMPUTER SCIENCE, 2022, 8