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Review
. 2024 May 11;16(5):e60119.
doi: 10.7759/cureus.60119. eCollection 2024 May.

Advancements in Artificial Intelligence for Precision Diagnosis and Treatment of Myocardial Infarction: A Comprehensive Review of Clinical Trials and Randomized Controlled Trials

Syed J Patel  1 , Salma Yousuf  2 , Jaswanth V Padala  3 , Shruta Reddy  4 , Pranav Saraf  5 , Alaa Nooh  6 , Luis Miguel A Fernandez Gutierrez  7 , Abdirahman H Abdirahman  8 , Rameen Tanveer  9 , Manju Rai  10
Affiliations
Review

Advancements in Artificial Intelligence for Precision Diagnosis and Treatment of Myocardial Infarction: A Comprehensive Review of Clinical Trials and Randomized Controlled Trials

Syed J Patel et al. Cureus. .

Abstract

Coronary artery disease (CAD) is still a serious global health issue that has a substantial impact on death and illness rates. The goal of primary prevention strategies is to lower the risk of developing CAD. Nevertheless, current methods usually rely on simple risk assessment instruments that might overlook significant individual risk factors. This limitation highlights the need for innovative methods that can accurately assess cardiovascular risk and offer personalized preventive care. Recent advances in machine learning and artificial intelligence (AI) have opened up interesting new avenues for optimizing primary preventive efforts for CAD and improving risk prediction models. By leveraging large-scale databases and advanced computational techniques, AI has the potential to fundamentally alter how cardiovascular risk is evaluated and managed. This review looks at current randomized controlled studies and clinical trials that explore the application of AI and machine learning to improve primary preventive measures for CAD. The emphasis is on their ability to recognize and include a range of risk elements in sophisticated risk assessment models.

Keywords: artificial intelligence; cardiovascular risk factors; coronary artery disease; machine learning; myocardial infarction; primary prevention; risk assessment.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Illustration of myocardial infarction caused by acute thrombus in the coronary artery.
Figure created with Biorender.com
Figure 2
Figure 2. Pathophysiology of myocardial infarction.
Common types of myocardial infarction (MI): Type 1 MI with acute coronary obstruction and Type 2 MI due to oxygen supply/demand mismatch without acute coronary obstruction (Figure is authors’ own creation).
Figure 3
Figure 3. AI in CVD: Diagnostic and therapeutic perspective.
ECG: Electrocardiograph; UCG: Ultrasonic cardiogram; CMR: cardiac magnetic resonance; CVD: cardiovascular disease; AI: artificial intelligence. Figure created from Biorender.com
Figure 4
Figure 4. AI-assisted acute myocardial infarction decision support system.
ECG: electrocardiogram; AI: artificial intelligence; ASAP score: altered consciousness, Systemic malaise, upper Abdominal pain, Past history; AI: artificial intelligence; STEMI: ST-segment elevation myocardial infarction; CV: cardiovascular. Figure created from Biorender.com
See this image and copyright information in PMC

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