Hypoglycemia event prediction from CGM using ensemble learning.
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ABSTRACT:
SUBMITTER: Fleischer J
PROVIDER: S-EPMC10012121 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Hypoglycemia event prediction from CGM using ensemble learning.
Fleischer Jesper J Hansen Troels Krarup TK Cichosz Simon Lebech SL
Frontiers in clinical diabetes and healthcare 20221209
This work sought to explore the potential of using standalone continuous glucose monitor (CGM) data for the prediction of hypoglycemia utilizing a large cohort of type 1 diabetes patients during free-living. We trained and tested an algorithm for the prediction of hypoglycemia within 40 minutes on 3.7 million CGM measurements from 225 patients using ensemble learning. The algorithm was also validated using 11.5 million synthetic CGM data. The results yielded a receiver operating characteristic a ...[more]
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