This workflow reads in the diabetes subset from the Dubosson data set, which contains glucose measurements, as well as several sensor measurements like heartrate, breathing rate, activity and acceleration. The exploration Component generates an overview of all the different measurements and lets the user filter the data by date and patient. To update the view without closing the window, the "Refresh Button" can be used. Afterwards an LSTM network is trained using 15 minutes of blood glucose measurements. The goal is to predict the next 15 minutes of blood glucose levels for each patient. The data is split into training and test set by taking 80% of the data for each patient from the top as training set and the remaining 20% as test set. "Diabetes_Patient_008" is not included in the training/testing process. This patient will be used for validation purposes. At the end, the model performance is displayed in an interactive view. In this view different Patient IDs can be selected and the corresponding Line Plot, as well as the RMSE score is shown. Also the results for "Diabetes_Patient_008", which is used for validation, is shown via a Line Plot.

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Hi Dear,
Would you mind please, guiding me on how can I access the dataset to run this workflow?

Can I know which dataset u used in this workflow,so I could run the workflow

Hello, I’ve got the workflow running until the model training component. Inside this component there is the KERAS Network Learner which cannot be configured because the “input deep learning network port object” is missing. I have no idea how to get this node working.