The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.
This research focuses on detecting the financial corruption cases in Iraq in light of adoption the strategic audit, the paper deals with the problem of the proliferation corruption cases particularly financial in Iraq and dramatically in the presence of audit and control devices as well as inspection and integrity devices, which indicates the existence of deficiencies and weaknesses in those devices in the implementation of audit and control functions in order to detect the corruption cases in the economic units in Iraq.
Stems objective of this research through the provision of approach of strategic audit concepts and indicate the extent importance of adopting of strategic audit as a means to detect the f
... Show MoreCox regression model have been used to estimate proportion hazard model for patients with hepatitis disease recorded in Gastrointestinal and Hepatic diseases Hospital in Iraq for (2002 -2005). Data consists of (age, gender, survival time terminal stat). A Kaplan-Meier method has been applied to estimate survival function and hazerd function.
ZM Al-Bahrani, Medico Legal Update, 2021
Receipt date: 2/2/2021 accepted date: 4/6/2021 Publication date: 12/31/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
The approval of the federal general budget in Iraq is one of the most important competencies of the legislative authority , Being one of the important financial and monetary policy instruments on which the state depends for its economic growth , Hence, the obstruction of the approval of the federal b
... Show MoreThe research aims to identify Determination talent management dimensions of (attracting talent, developing talent, directing talent, performance management talent, retain talent) in the entrepreneurial performance of the organization dimensions of (advance planning, efficiency, effectiveness), so search occupies the extreme importance of being treated important and recent issue of the performance Entrepreneuria, management talent, aware of the importance of the subject and expected results of the company surveyed, was an analysis of data obtained through field visits in addition to the questionnaire and interviews, highlights were the results that have been reached to take the sample into account all the management requirements knack of att
... Show MoreThe approval of the federal general budget in Iraq is one of the most important competencies of the legislative authority , Being one of the important financial and monetary policy instruments on which the state depends for its economic growth , Hence, the obstruction of the approval of the federal budget due to sectarian quotas, the absence of national interest, and the emergence of bargaining processes between political parties belonging to the regions and sectarianism , As well as the absence of economic plans and programs as a result of non-cognition and understanding of the nature of its supposed political system applied in Iraq and the absence of specialists would le
... Show MoreAround 65 million individuals suffer from epilepsy worldwide, and when it is not properly treated, it is linked to higher rates of physical harm and mortality. Due to the requirement for long‐term therapy and the side effects of many medications, medication compliance is a significant issue. The purpose of this review was to summarize the findings of previous studies examining the quality of life (QOL), adherence, patient education, and medication knowledge, as well as the impact of a pharmacist‐led educational intervention. Additionally, to find out if these studies benefit epileptic patients, to find the appropriate method used to help them in all aspects of their lives, and to use these in future studies. A systematic and comprehensi
... Show MoreSensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
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