Thesis supervisor: István Vassányi
co-supervisor: István Kósa
Location of studies (in Hungarian): University of Pannonia, H-8200 Veszprém, Egyetem u. 10. Hungary Abbreviation of location of studies: PE
Description of the research topic:
Diabetes Mellitus outpatients worldwide would benefit from a lifestyle support tool that delivers reliable short term Blood Glucose Level (BGL) predictions. The aim of the research is to develop a method for after-meal BGL prediction based on only the baseline BGL, the insulin dosing and a dietary log. The work builds on previous research at MIRDC with promising results in the field of absorption and BGL model based prediction. The task of the applicant is to extend the existing signal processing framework using state of the art neural network training methods like ensemble learning, thus trying to improve the accuracy of the prediction.
Papers related to the topic:
1. Rebaz A.H.Karim, István Vassányi, István Kósa. After-meal blood glucose level prediction using an absorption model for neural network training. Computers in Biology and Medicine, 2020, https://doi.org/10.1016/j.compbiomed.2020.103956
2. Péter Gyuk, István Vassányi and István Kósa. Blood Glucose Level Prediction for Diabetics Based on Nutrition and Insulin Administration Logs Using Personalized Mathematical Models. Journal of Healthcare Engineering, Volume 2019, Article ID 8605206, https://doi.org/10.1155/2019/8605206
Required language skills: english Number of students who can be accepted: 1
Deadline for application: 2021-02-28
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
Login
