Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18912, first published .
A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism

Ashenafi Zebene Woldaregay   1 , MSc ;   Ilkka Kalervo Launonen   2 , PhD ;   David Albers   3, 4 , PhD ;   Jorge Igual   5 , PhD ;   Eirik Årsand   1 , PhD ;   Gunnar Hartvigsen   1 , PhD

1 Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway

2 Department of Clinical Research, University Hospital of North Norway, Tromsø, Norway

3 Department of Pediatrics, Informatics and Data Science, University of Colorado, Aurora, CO, United States

4 Department of Biomedical Informatics, Columbia University, New York, NY, United States

5 Universidad Politecnica Valencia, Valencia, Spain

Corresponding Author:

  • Ashenafi Zebene Woldaregay, MSc
  • Department of Computer Science
  • University of Tromsø – The Arctic University of Norway
  • Hansine Hansens veg 54, Science building Realfagbygget, office A124
  • Tromsø
  • Norway
  • Phone: 47 46359333
  • Email: ashenafi.z.woldaregay@uit.no