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Blood Glucose Prediction Using Convolutional Long Short-Term Memory Algorithms
Diabetes Mellitus is one of the preeminent causes of death to date. Effective procedures are necessary to prevent diabetes and avoid complications that may cause early death. A common approach is to control patient blood glucose, which necessitates a periodic measurement of blood glucose concentration. This study developed a blood glucose prediction system using a convolutional long short-term memory (Conv-LSTM) algorithm. Conv-LSTM is a variation of LSTM algorithms that are suitable for use indoi:10.23917/khif.v7i2.14629 fatcat:cy2elka4cnfe7lusdukuppemmi