Forewarning Postprandial Hyperglycemia with Interpretations using Machine Learning

Asiful Arefeen, Samantha Fessler, Carol Johnston, Hassan Ghasemzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Postprandial hyperglycemia (PPHG) is detrimental to health and increases risk of cardiovascular diseases, reduced eyesight, and life-threatening conditions like cancer. Detecting PPHG events before they occur can potentially help with providing early interventions. Prior research suggests that PPHG events can be predicted based on information about diet. However, such computational approaches (1) are data hungry requiring significant amounts of data for algorithm training; and (2) work as a black-box and lack interpretability, thus limiting the adoption of these technologies for use in clinical interventions. Motivated by these shortcomings, we propose, DietNudge1, a machine learning based framework that integrates multi-modal data about diet, insulin, and blood glucose to predict PPHG events before they occur. Using data from patients with diabetes, we demonstrate that our model can predict PPHG events with up to 90% classification accuracy and an average F1 score of 0.93. The proposed decision-tree-based approach also identifies modifiable factors that contribute to an impending PPHG event while providing personalized thresholds to prevent such events. Our results suggest that we can develop simple, yet effective, computational algorithms that can be used as preventative mechanisms for diabetes and obesity management.

Original languageEnglish (US)
Title of host publicationBHI-BSN 2022 - IEEE-EMBS International Conference on Biomedical and Health Informatics and IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665487917
DOIs
StatePublished - 2022
Event2022 IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, BSN 2022 - Ioannina, Greece
Duration: Sep 27 2022Sep 30 2022

Publication series

NameBHI-BSN 2022 - IEEE-EMBS International Conference on Biomedical and Health Informatics and IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks - Proceedings

Conference

Conference2022 IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, BSN 2022
Country/TerritoryGreece
CityIoannina
Period9/27/229/30/22

Keywords

  • continuous glucose monitor
  • decision tree
  • diabetes
  • Machine learning
  • postprandial hyperglycemia

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Biomedical Engineering
  • Instrumentation

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