A Systematic Review: Do the Use of Machine Learning, Deep Learning, and Artificial Intelligence Improve Patient Outcomes in Acute Myocardial Ischemia Compared to Clinician-Only Approaches?

Abstract

Cardiovascular diseases (CVDs) present a significant global health challenge and remain a primary cause of death. Early detection and intervention are crucial for improved outcomes in acute coronary syndrome (ACS), particularly acute myocardial infarction (AMI) cases. Artificial intelligence (AI) can detect heart disease early by analyzing patient information and electrocardiogram (ECG) data, providing invaluable insights into this critical health issue. However, the imbalanced nature of ECG and patient data presents challenges for traditional machine learning (ML) algorithms in performing unbiasedly. Investigators have proposed various data-level and algorithm-level solutions to overcome these challenges. In this study, we used a systematic literature review (SLR) approach to give an overview of the current literature and to highlight the difficulties of utilizing ML, deep learning (DL), and AI algorithms in predicting, diagnosing, and prognosis of heart diseases. We reviewed 181 articles from reputable journals published between 2013 and June 15, 2023, focusing on eight selected papers for in-depth analysis. The analysis considered factors such as heart disease type, algorithms used, applications, and proposed solutions and compared the benefits of algorithms combined with clinicians versus clinicians alone. This systematic review revealed that the current ML-based diagnostic approaches face several open problems and issues when implementing ML, DL, and AI in real-life settings. Although these algorithms show higher sensitivities, specificities, and accuracies in detecting heart disease, we must address the ethical concerns while implementing these models into clinical practice. The transparency of how these algorithms operate remains a challenge. Nevertheless, further exploration and research in ML, DL, and AI are necessary to overcome these challenges and fully harness their potential to improve health outcomes for patients with AMI.

Role of Cardiac Rehabilitation in Improving Outcomes After Myocardial Infarction

“…Myocardial infarction happens as a result of a partial or complete blockage of blood flow (coronary) to the heart muscle, leading to the ischemic death of the tissue supplied by that artery. Acute myocardial infarction (AMI) is classified into two types based on ECG findings: ST-segment elevated myocardial infarction (STEMI) and non-ST-segment elevated myocardial infarction (NSTEMI) [1]. STEMI occurs due to total occlusion of the blood flow [1], requiring the emergent treatment of percutaneous coronary intervention [PCI] or fibrinolytic therapy [2].…”

“…Acute myocardial infarction (AMI) is classified into two types based on ECG findings: ST-segment elevated myocardial infarction (STEMI) and non-ST-segment elevated myocardial infarction (NSTEMI) [1]. STEMI occurs due to total occlusion of the blood flow [1], requiring the emergent treatment of percutaneous coronary intervention [PCI] or fibrinolytic therapy [2]. The primary aim of the healthcare system is to quickly identify and treat individuals experiencing STEMI, ensuring that the administration of fibrinolytic therapy begins within 30 minutes of medical contact (door-to-needle) or a PCI procedure starts within 90 minutes of medical contact (door-toballoon), as demonstrated in Figure 1 [2].…”

“…The primary aim of the healthcare system is to quickly identify and treat individuals experiencing STEMI, ensuring that the administration of fibrinolytic therapy begins within 30 minutes of medical contact (door-to-needle) or a PCI procedure starts within 90 minutes of medical contact (door-toballoon), as demonstrated in Figure 1 [2]. An NSTEMI occurs due to subtotal occlusion of blood flow [1], which allows some flow of blood to the tissue. As AMI is one of the most common cardiovascular diseases (CVDs), it continues to pose a significant health burden globally.…”