# Comparison of Monkeypox and Wart DNA Sequences with Deep Learning Model
## 3 Application Results and Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**DNA-Mapping Methods** & **Accuracy Rate** & **Precision Rate** & **Recall Rate** & **F1-Score** \\ \hline Atomic number & 95.57\% & 100\% & 99.44\% & 99.71\% \\ EIIP & 97.65\% & 99.92\% & 100\% & 99.95\% \\ Integer number & 99.50\% & 100\% & 99.53\% & 99.76\% \\ Molecular mass & 95.84\% & 100\% & 99.53\% & 99.76\% \\ Reel number & 91.85\% & 99.91\% & 100\% & 99.95\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Classification performances of DNA-mapping methods. chemical properties of the bases. The reason why this method was less ineffective than real number and molecular mass DNA-mapping methods may be that the chemical properties of bases were not used in the study. The use of chemical properties may increase the performance of this method. The most effective classification process was carried out with the EIIP and integer number DNA-mapping methods. The EIIP DNA-mapping method is a physicochemical-based method just like the atomic number DNA-mapping method. The reason why this method was successful over the atomic number DNA-mapping method may be that its size takes up less space. In artificial intelligence applications, the size of the data is of great importance and affects the classification performance. In addition, the use of chemical properties of bases may positively affect the performance of this method. The most effective classification result was obtained by the integer number DNA-mapping method. In this method, the mapping process is not based on specific information. However, it is a method often used in artificial intelligence applications. The main reason for this is that the deviations are symmetrical in this method [19]. This has a positive effect on the performance of the classifier. Figure 2: Confusion matrix results of DNA-mapping methods. (**a**) Atomic number, (**b**) EIIP, (**c**) Integer number, (**d**) Molecular mass, (**e**) Real number. The advantages and disadvantages of the study can be expressed as follows:  
* The number of data is of great importance in deep learning studies. Although the number of data used in this study was small, an effective classification process was carried out. In the future, the DNA sequences of the virus will multiply, and more data will be obtained. Since the results of the classification process with more data will be healthier, the results of the findings obtained in this study may vary. * Furthermore, only one of the deep learning models, the BiLSTM model, was used in this study. The use of different deep learning models or the use of machine learning algorithms will pave the way for the comparison of the study in terms of the literature and will show the effect of computer-aided approaches. * Finally, it is sometimes difficult to determine whether human bumps are monkeypox or warts. Even experienced specialists cannot distinguish them clearly in some cases, and this may cause the diagnosis and treatment to be wrong. Diagnosis based on DNA sequences, which was the starting point of this study, was more effective. In this way, the distinction between these two diseases can be made clearly. Obtaining the DNA sequence of the disease seen in the body and analyzing this sequence with computer-aided applications will be healthier in terms of both diagnosis and confidence. The application results obtained support this. * The performance of the model varied according to the DNA-mapping methods used. This reveals the biggest limitation of this study. The absence of a standard method and the variation in the model according to the mapping methods reduce the applicability of the model. It takes time to identify and implement an appropriate mapping method. * In this study, raw DNA sequences were used and classified only by mapping methods. Performance can be increased by applying various feature extraction operations (signal processing, image processing, etc.). * In addition, a secure and distributed environment can be created to share data.