## 1 Introduction
On the other hand, posterior lead interpretation was applied to 28 patients (Group B, 15.1%) for the diagnosis of STEMI requiring reperfusion therapy. In clinical practice, 15 leads ECG leads have better diagnoses in STEMI condition than the 12 leads ECG signal which was not conclusive (OR = 2.43, \(p\) = 0.04). It can be concluded that the use of 15 lead ECG signals contributes to a faster and more accurate diagnosis of STEMI, especially in the Emergency Unit. The study of 15 ECG leads was also conducted by [PERSON] [11]. The study aimed to investigate the diagnostic and therapeutic impact of 15 ECG leads (15 EKG) in the Emergency Department (ED) for patients suffering from chest pain (CP). The study design was a prospective use of 15 ECG with real-time physician survey and retrospective comparison with 12 ECG leads (12 EKG). The result of this study is that of the 15 ECG cases, 81% have completed the doctor's survey and showed that the results of the diagnosis and management of ACIS were not changed by 15 ECGs. However, clinicians feel that the 15 ECG provides a more complete anatomical picture of ACIS especially the description of myocardial injury without changing the ED diagnosis, ED-based therapy, or hospital disposition in adult CP patients. The investigators suggest conducting further studies to identify a subset of patients who might benefit from a 15 EKG. Another study was carried out by [PERSON] [12], which was designed to evaluate ST-segment deviation of the posterior lead ECG in ACS patients at Beheshti Hospital in 2002. This study was conducted on 347 ACS patients admitted to the Emergency Department. Diagnosed on 15 ECG leads (12 standard ECG leads with an additional three leads (V7-V8-V9)) and performed statistical analysis, calculated percentage sensitivity, odds ratios, 95% confidence interval. The results showed that 15 lead ECG provides increased sensitivity in detecting ST-segment deviation in AMI and unstable angina. This study performs 10 MI classes classification using 1D-CNN on 15 leads ECG leads. Moreover, in order to get better performance a framework based on 1D-CNN architecture was develop. In order to reduce the computational complexity and cost, the proposed CNN architecture was constructed using two convolutional layers. Moreover, 700 nodes of ECGsignal are used to provide a better feature representative. Based on the description above, this research and the proposed method provide new contributions as follows:  
* Propose an automatic classification framework for Myocardial Infarction (MI) with 15 leads ECG signal. * Developing a simple 1D-CNN architecture for classifying 10 MI classes and Normal classes. In measuring and evaluating the proposed method, we will analyze the performance of the model based on the values of accuracy, sensitivity, specificity, precision, and F1 score. With a detailed approach and to describe the proposed methods and contributions, this paper is structured as follows: In Section 2, we present the proposed materials and methods for ECG imaging in identifying MI. In Section 3, we present the results of applying the method. In Section 4. we present a discussion. Finally, Section 5 draws conclusions from the process and the results obtained.