## 3 Proposed Methodology
### Classification of MANN-AM (Modified Artificial Neural Network with Attention Mechanism)
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **Accuracy** & **Precision** & **F1-Score** & **Specificity** & **Sensitivity** \\ \hline XGBoost (existing) [32] & 0.9145 & 0.9549 & 0.9012 & 0.9596 & 0.8479 \\ Random Forest & 0.8149 & 0.886 & 0.8126 & 0.8945 & 0.7446 \\ MLP & 0.8395 & 0.8546 & 0.8478 & 0.8446 & 0.8349 \\ K-NN & 0.7718 & 0.9125 & 0.7508 & 0.9456 & 0.6256 \\ SVM & 0.8515 & 0.8945 & 0.8564 & 0.8945 & 0.8143 \\
**Proposed system** & **0.99** & **1** & **0.99** & **0.99** & **1** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of performance metrics of classifiers [32]. Figure 13: Comparison of performance metrics of classifiers [32]. proposed methodology exposed a higher accuracy rate than the other three algorithms. Further, a confusion matrix was attained to showcase the correct classification rates of the proposed system. In addition, for evaluating the efficacy of the proposed system, a comparison was performed with two conventional studies. The comparative analysis outcomes confirmed the proposed work was more effective than existing studies, with 0.99 as the accuracy rate. Due to the high prediction rate, the study possesses the ability to be applied in real-time. Moreover, in the future, various other hybrid ML algorithms could be regarded to enhance the prediction rate. Additionally, the proposed system can be deployed in real-world scenarios such as public restrooms, hospitals and offices, which will increase the effectiveness and feasibility of diagnosing UTIs. Conceptualization, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; methodology, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; software, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; validation, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; formal analysis, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; investigation, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; resources, A. A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; data curation, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; writing--original draft preparation, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; writing--review and editing, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; visualization, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; supervision, A.A., S.A., A.B., M.S., A.G. and Y.-D.Z. ; project administration, A.A., S.A. and A.B. ; funding acquisition, A.A., S.A., A.B., M.S. and A.G. All authors have read and agreed to the published version of the manuscript. The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia, for funding this research work through the project number (IF2/PSAU/2022/01/22929). Not applicable. The authors declare no conflict of interest. ## References

* _[PERSON] et al. (2022)_ [PERSON]; [PERSON]; [PERSON] [PERSON] Advancing e-Government using Internet of Things. In _Mobile Computing and Sustainable Informatics_; Springer: Berlin/Heidelberg, Germany, 2022; pp. 123-137. * _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON] [PERSON] Altalk: A tutorial to implement AI as IoT devices. _IET Netw._**2019**, \(8\), 195-202. [CrossRef]
* _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Impact of cloud computing and internet of things on the future internet. _Technol. Rep. Kansai Univ._**2020**, _62_, 2179-2190. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON] Industry 4.0 and health: Internet of things, big data, and cloud computing for healthcare 4.0. _J. Ind. Inf. Integr._**2020**, _18_, 100129. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] The Internet of Things for Smart Cities: Technologies and Applications. _IEEE Netw._**2019**, _33_, 4-5. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON] Internet of Things: A survey of enabling technologies in healthcare and its applications. _Comput. Networks_**2019**, _153_, 113-131. [CrossRef]
* [PERSON] (2019) [PERSON] The Big Picture on the \"AI Turn\" for Digital Health: The Internet of Things and Cyber-Physical Systems. _OMICS J. Integr. Biol._**2019**, _23_, 308-311.