METHOD AND MEANS FOR POSTPRANDIAL BLOOD GLUCOSE LEVEL PREDICTION

Method and means for postprandial blood glucose level prediction The invention relates to a method (100) for predicting blood glucose levels, in particular for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving (101) a first medical data set of a patient covering a time range, said first medical data set comprising glucose data and further other medical data of said patient, extracting (102) a second medical data set from said first medical data set, wherein the second medical data set is a subset of the first medical data set and wherein the extracting comprises at least one of: identifying (103) duplicates in the first medical data set and removing identified duplicates, identifying (104) data values that lie above a predefined maximum threshold data value or identifying (105) data values that lie below a predefined minimum threshold data value and removing data associated to said identified data values, identifying (106) data values that differ from predetermined expected data values by more than a predetermined amount and removing data associated to said identified data values, identifying (107) incomplete data for which data values are missing and removing identified incomplete data, identifying (108) at least one predetermined time-dependent data pattern and removing data associated to said identified time-dependent data pattern, providing (109) the extracted second medical data set as input to a blood glucose level prediction model, and predicting (110) future blood glucose levels of the patient using the output of the blood glucose level prediction model based on the second medical data set. L'invention concerne un procédé et un moyen de prédiction de taux de glycémie postprandiale et un procédé (100) de prédiction de taux de glycémie, en particulier pour une prédiction de taux de glycémie postprandiale, le procédé étant implémenté par ordinateur et comprenant les étapes suivantes : recevoir (101) un premier ensemble de données médicales d'un patient couvrant un intervalle de temps, ledit premier ensemble de données médicales comprenant des données de glucose et d'autres données médicales dudit patient, extraire (102) un second ensemble de données médicales dudit premier ensemble de données médicales, le second ensemble de données médicales étant un sous-ensemble du premier ensemble de données médicales et l'extraction comprenant au moins l'une des actions suivantes : identifier (103) des do