A probabilistic concept annotation for IT service desk tickets
Ea-Ee Jan, Kuan-Yu Chen, et al.
ESAIR 2014
Nocturnal hypoglycemia is a serious complication of insulin-treated diabetes, which commonly goes undetected. Continuous glucose monitoring (CGM) devices have enabled prediction of impending nocturnal hypoglycemia, however, prior efforts have been limited to a short prediction horizon (~ 30 minutes). To this end, a nocturnal hypoglycemia prediction model with a 6-hour horizon (midnight-6 am) was developed using a random forest machine- learning model based on data from 10,000 users with more than 1 million nights of CGM data. The model demonstrated an overall nighttime hypoglycemia prediction performance of ROC AUC = 0.84, with AUC = 0.90 for early night (midnight-3 am) and AUC = 0.75 for late night (prediction at midnight, looking at 3-6 am window). While instabilities and the absence of late-night blood glucose patterns introduce predictability challenges, this 6-hour horizon model demonstrates good performance in predicting nocturnal hypoglycemia. Additional study and specific patient-specific features will provide refinements that further ensure safe overnight management of glycemia.
Ea-Ee Jan, Kuan-Yu Chen, et al.
ESAIR 2014
Tsuyoshi Idé, Naoki Abe
KDD 2023
Ea-Ee Jan, Kuan-Yu Chen, et al.
IM 2015
Takayuki Osogami, T. Imamichi, et al.
IBM J. Res. Dev