Cristin-resultat-ID: 1739766
Sist endret: 21. november 2019 09:11
NVI-rapporteringsår: 2019
Resultat
Vitenskapelig artikkel
2019

Food Recommendation Using Machine Learning for Physical Activities in Patients with Type 1 Diabetes.

Bidragsytere:
  • Phuong Ngo
  • Maryam Tayefi
  • Anne Torill Nordsletta og
  • Fred Godtliebsen

Tidsskrift

Linköping Electronic Conference Proceedings
ISSN 1650-3686
e-ISSN 1650-3740
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2019
Artikkelnummer: 008

Beskrivelse Beskrivelse

Tittel

Food Recommendation Using Machine Learning for Physical Activities in Patients with Type 1 Diabetes.

Sammendrag

Physical activities have a significant impact on blood glucose homeostasis of patients with type 1 diabetes. Regular physical exercise provides many proven health benefits and is recommended as part of a healthy lifestyle. However, one of the main side effects of physical activities is hypoglycemia (low blood glucose). Fear of hypoglycemia generally leads to the patients not participating in physical activities. This paper shows a proof of concept that machine learning can be used to create a personalized food recommendation system for patients with type 1 diabetes. Machine learning algorithms were designed to improve glycemic control and reduce the overcompensation of carbohydrate. First, a personalized model based on feedforward neural networks is developed to predict the blood glucose outcome during and after physical activities. Based on the personalized model and reinforcement learning, optimal food intakes will be recommended to the patient. Simulation results show that the proposed methodology has successfully maintained the blood glucose in the healthy range on a type 1 diabetes simulator during physical activities.

Bidragsytere

Phuong Ngo

  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF

Maryam Tayefi

  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF

Anne Torill Nordsletta

  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF

Fred Godtliebsen

  • Tilknyttet:
    Forfatter
    ved Institutt for matematikk og statistikk ved UiT Norges arktiske universitet
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