Deep Multi-Output Forecasting: Learning to Accurately Predict Blood
Glucose Trajectories

Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories

14 June 2018

Papers citing "Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories"

17 / 17 papers shown

Title
GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks Renat Sergazinov Elizabeth Chun Valeriya Rogovchenko Nathaniel Fernandes Nicholas Kasman I. Gaynanova AI4TS 29 3 0 08 Oct 2024
A Survey on Privacy of Health Data Lifecycle: A Taxonomy, Review, and Future Directions Sunanda Bose D. Marijan 19 3 0 09 Nov 2023
Likelihood-based generalization of Markov parameter estimation and multiple shooting objectives in system identification Nicholas Galioto Alex Arkady Gorodetsky 31 1 0 20 Dec 2022
Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification Renat Sergazinov Mohammadreza Armandpour I. Gaynanova BDL AI4TS MedIm 38 11 0 09 Sep 2022
EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous Variables Penglei Gao Xi Yang Rui Zhang Ping Guo John Y. Goulermas Kaizhu Huang AI4TS 21 5 0 03 Aug 2022
Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent Neural Networks Mohammadreza Armandpour Brian Kidd Yu Du Jianhua Z. Huang 16 14 0 02 Jun 2021
Recursive input and state estimation: A general framework for learning from time series with missing data Alberto García-Durán Robert West AI4TS 17 2 0 17 Apr 2021
Deep Time Series Forecasting with Shape and Temporal Criteria Vincent Le Guen Nicolas Thome AI4TS 32 27 0 09 Apr 2021
Domain Adaptation for Time Series Forecasting via Attention Sharing Xiaoyong Jin Youngsuk Park Danielle C. Maddix Bernie Wang Xifeng Yan TTA OOD AI4TS 104 75 0 13 Feb 2021
Stacked LSTM Based Deep Recurrent Neural Network with Kalman Smoothing for Blood Glucose Prediction Md Fazle Rabby Yazhou Tu Md. Imran Hossen Insup Lee Anthony Maida X. Hei 32 114 0 18 Jan 2021
Do We Really Need Deep Learning Models for Time Series Forecasting? Shereen Elsayed Daniela Thyssens Ahmed Rashed H. Jomaa Lars Schmidt-Thieme AI4TS 16 105 0 06 Jan 2021
Explainable Tensorized Neural Ordinary Differential Equations forArbitrary-step Time Series Prediction Penglei Gao Xi Yang Rui Zhang Kaizhu Huang AI4TS 14 15 0 26 Nov 2020
Deep Reinforcement Learning for Closed-Loop Blood Glucose Control Ian Fox Joyce M. Lee R. Pop-Busui Jenna Wiens BDL OffRL 22 50 0 18 Sep 2020
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models Vincent Le Guen Nicolas Thome AI4TS 32 134 0 19 Sep 2019
Using Contextual Information to Improve Blood Glucose Prediction Mohammad Akbari R. Chunara 14 6 0 24 Aug 2019
A Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular Disorders N. Hurley E. Spatz H. Krumholz R. Jafari B. Mortazavi 19 1 0 12 Aug 2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data Tian Guo Tao R. Lin Nino Antulov-Fantulin AI4TS 26 154 0 28 May 2019