Convolutional Recurrent Neural Networks for Glucose Prediction


Blood glucose control is critical for diabetes management. Machine Learning techniques are used in current digital therapy approaches for people with type 1 diabetes, such as the artificial pancreas and insulin bolus calculators, to anticipate subcutaneous glucose for better control. Deep Learning has lately been used in healthcare and medical research to obtain cutting-edge outcomes in a variety of tasks, including disease diagnosis and patient condition prediction. We present a Deep Learning model capable of forecasting glucose levels with leading accuracy for simulated patient cases (RMSE = 9.38 0.71 [mg/dL] over a 30-min horizon, RMSE = 18.87 2.25 [mg/dL] over a 60-min horizon) and real patient cases (RMSE = 21.07 2.35 [mg/dL] for 30 minutes, RMSE = 33.27 4.79 percent for 60 minutes). Furthermore, in both a simulated patient dataset (PH eff = 29.0 0.7 for 30 min and PHeff = 49.8 2.9 for 60 min) and a real patient dataset (PH eff = 19.3 3.1 for 30 min and PH eff = 29.3 9.4 for 60 min), the model provides competitive performance in providing effective prediction horizon (PHeff) with minimal time lag. This method is tested using a clinical dataset of ten real cases, each including glucose readings, insulin bolus, and meal (carbohydrate) data, as well as a dataset of ten simulated cases created from the UVA/Padova simulator. Four techniques are used to compare the performance of the recurrent convolutional neural network. The suggested technique is implemented on an Android smartphone, with an execution time of 6 milliseconds on a phone against 780 milliseconds on a laptop.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal ABSTRACT: The most important goal of diabetes treatment is to keep blood glucose levels in the euglycemic range, preventing or at
PROJECT TITLE :Influence of glucose as a contaminant on discharge characteristics of HVAC insulatorABSTRACT:Contaminant is the most factor affecting the insulation performance. The contaminant composition determines the inception
PROJECT TITLE : Video Dissemination over Hybrid Cellular and Ad Hoc Networks - 2014 ABSTRACT: We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate
PROJECT TITLE : Sleep Scheduling for Geographic Routing in Duty-Cycled Mobile Sensor Network - 2014 ABSTRACT: Recently, the research focus on geographic routing, a promising routing scheme in wireless sensor networks (WSNs),
PROJECT TITLE : Security Analysis of Handover Key Management in 4G LTESAE Networks - 2014 ABSTRACT: The goal of 3GPP Long Term Evolution/System Architecture Evolution (LTE/SAE) is to move mobile cellular wireless technology

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry