# Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models

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## Abstract

**:**

## 1. Introduction

## 2. State of the Art

## 3. Materials and Methods

#### 3.1. Dataset Used

#### 3.2. Proposed Model

## 4. Experimental Results

#### 4.1. Software Configuration

#### 4.2. Numerical Results

#### 4.3. Using a Simple Model Results

^{−1}vs. 0.57 h

^{−1}). The quality of the generated absorption curve for the fast insulin is measured by computing the mean absolute error for the difference between the generated curve and the curve computed by the AIDA2 simulator. Table 4 captures a value of 0.088 for the single layer RNN model which is higher than the 0.077 value in Table 3 for the two-layer RNN model.

## 5. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 6.**Mean, min, and max prediction errors for the individuals computed at each epoch by the genetic algorithm for one patient generated by the AIDA2 simulator.

**Figure 9.**Mean, min, and max prediction errors for the individuals computed at each epoch by the genetic algorithm for the same patient in Figure 5 generated by the AIDA2 simulator.

Parameter | Value |
---|---|

Number of simulated patients | 40 |

Number of days per patient | 8 |

Average number of insulin boluses per day | 4 |

Average number of meals per day | 6 |

Layer (Type) | Output Shape | #Param |
---|---|---|

lstm_1 (LSTM) | (None, 16, 10) | 600 |

dropout (Dropout) | (None, 16, 10) | 0 |

lstm_2 (LSTM) | (None, 5) | 320 |

dropout_1 (Dropout) | (None, 5) | 0 |

dense (Dense) | (None, 3) | 18 |

dense_1 (Dense) | (None, 1) | 4 |

Parameter | Value |
---|---|

Mean peak time (h) | 1.52 |

Mean decay rate (h^{−1}) | 0.57 |

Mean absolute error | 0.078 |

Parameter | Value |
---|---|

Mean peak time (h) | 1.65 |

Mean decay rate (h^{−1}) | 0.77 |

Mean absolute error | 0.088 |

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**MDPI and ACS Style**

Muñoz-Organero, M.; Queipo-Álvarez, P.; García Gutiérrez, B.
Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models. *Sensors* **2021**, *21*, 4926.
https://doi.org/10.3390/s21144926

**AMA Style**

Muñoz-Organero M, Queipo-Álvarez P, García Gutiérrez B.
Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models. *Sensors*. 2021; 21(14):4926.
https://doi.org/10.3390/s21144926

**Chicago/Turabian Style**

Muñoz-Organero, Mario, Paula Queipo-Álvarez, and Boni García Gutiérrez.
2021. "Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models" *Sensors* 21, no. 14: 4926.
https://doi.org/10.3390/s21144926