Abstract:
CMRI is the exclusive imaging technique capable of identifying myocardial edema, endomyocardial fibrosis, pericarditis accompanied by pericardial effusions, and apical thrombi within either the left or right ventricle. In this work, we examine the research literature on the use of CMRI in the diagnosis of chest discomfort, employing randomized controlled trials (RCTs) to evaluate its effectiveness. The research outlines the disorders of the chest and the machine learning approaches for detecting them. In conclusion, the study ends with an examination of a fundamental illustration of CMRI analysis. To find a comprehensive review, the Scopus scientific resource is analyzed. The issue, based on the findings, is to distinguish ischemia from non-ischemic cardiac causes of chest pain in individuals presenting with sudden chest pain or discomfort upon arrival at the emergency department (ED). Due to the failure of conventional methods in accurately diagnosing acute cardiac ischemia, individuals are still being inappropriately discharged from the ED, resulting in a heightened death rate.
摘要:
CMRI是能够识别心肌水肿的独家成像技术,心内膜心肌纤维化,心包炎伴有心包积液,左心室或右心室内的心尖血栓。在这项工作中,我们研究了关于CMRI在胸部不适诊断中的应用的研究文献,采用随机对照试验(RCTs)评估其有效性。该研究概述了胸部疾病以及检测它们的机器学习方法。总之,该研究以对CMRI分析的基本说明的检查结束。为了找到一个全面的审查,对Scopus科学资源进行了分析。问题,根据调查结果,在到达急诊科(ED)时出现突然胸痛或不适的个体中,将缺血与非缺血性心脏原因的胸痛区分开。由于常规方法不能准确诊断急性心肌缺血,个人仍被不适当地从急诊室出院,导致死亡率上升。