## 7 Conclusions  
The paper presented Tesseratus, a hybrid model that adopts a multi-agent approach to address the problem of predicting glucose concentration for T1D individuals. Tesseratus has reactive and intelligent agents, where the reactive agents act as sensors and monitors, and intelligent agents act as an oracle or as an apprentice. The oracle knowledge is provided by a mathematical model for the HGIRS and it transfers knowledge to the apprentice, which \begin{table}
\begin{tabular}{c c c} \hline \hline
**PH** & **[PERSON] et al., 2019 [58] (\%)** & **Tesseratus (\%)** \\ \hline
30 min & 7 & 14.43 \\ \hline
60 min & 16.8 & 22.78 \\ \hline
120 min & 32.7 & **28.04** \\ \hline
180 min & 45 & **31.19** \\ \hline
360 min & 44.2 & **36.49** \\ \hline
420 min & – & **32** \\ \hline
480 min & – & **25.33** \\ \hline \hline \end{tabular}
\end{table} 
Table 11: MAPE at nighttime comparison between [PERSON] et al., 2019 [58] and Tesseratus—21 days of training. also learn from data provided by sensors and monitors. Tesseratus uses a dual continuous learning model that can mitigate errors between the predicted and continuously measured values, in addition to the ODE's own input parameters. The combination of techniques is advantageous, as it consists of models with complementary functions, resulting in a cohesive, well-adjusted model capable of generalization. Tesseratus was validated with seven real T1D Brazilian individuals that provided their data collected for up to 21 days: the seven initial days were used to personalize the model and the following days were used to validate the model capacity of predicting glucose oscillation for a PH that ranges from 15 min to 4 h during daytime and from 15 min to 8 h at night-time. As the evaluation of the MAE indicates, Tesseratus is able to predict glucose oscillation with an accuracy equal to or less than 30 mg/dL (1.7 mmol/L). As future work, it is our intention to continuously improve the performance of the Tesseratus while reducing the error of the predicted value by removing some specific restrictions found in the literature: (a) constant values of parameters from mathematical models for prediction calculations; (b) agent's support for continuous learning and ODE parameter values correction; (c) barriers to combining different prediction models, using active learning, reusing, combining and adapting knowledge from different agents [66]. Some limitations need to be addressed in future work, such as: (1) it does not support pregnant women and type 2 individuals with diabetes mellitus; (2) for now, it only supports four types of insulin analogues: aspart, lispro, glargine and degludec; (3) the dataset is still small, performed with historical data for only seven real individuals; (4) few insulin sensors or pumps were tested during the research, according to Table 4; (5) it is necessary to test with new variables: stress, hormonal effects, blood oxygen and heart rate; (6) it is necessary to analyze blood glucose and insulin concentration associated with comorbidities. Conceptualization, J.P.A.P., A.A.F.B., J.d.S.B. and M.L.C.C.-G.; methodology, J.P.A.P. and A.A.F.B. ; software, J.P.A.P., validation, J.P.A.P. and J.d.S.B. ; formal analysis, J.P.A.P. and J.d.S.B. ; investigation, J.P.A.P. ; resources, J.P.A.P. and A.A.F.B. ; data curation, J.P.A.P. ; writing--original draft preparation, J.P.A.P. ; writing--review and editing, J.P.A.P., A.A.F.B., J.d.S.B. and M.L.C.C.-G.; visualization, J.P.A.P. ; supervision, A.A.F.B. ; project administration, J.P.A.P. and A.A.F.B. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of the University Hospital of Sao Paulo (HU-USP) (protocol code 1819188--approved on 24 September 2021), for studies involving humans. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study (Free and Informed Consent Term). Not applicable.