Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature
Acute coronary syndrome (ACS) is a global health concern that requires rapid and accurate diagnosis for timely intervention and better patient outcomes. With the emergence of Artificial Intelligence (AI), significant advancements have been made in improving diagnostic accuracy, efficiency, and risk...
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| Format: | Article |
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MDPI AG
2025-03-01
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| Online Access: | https://www.mdpi.com/2075-1729/15/4/515 |
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| author | Andrea Mariani Carmen Anna Maria Spaccarotella Francesco Saverio Rea Anna Franzone Raffaele Piccolo Domenico Simone Castiello Ciro Indolfi Giovanni Esposito |
| author_facet | Andrea Mariani Carmen Anna Maria Spaccarotella Francesco Saverio Rea Anna Franzone Raffaele Piccolo Domenico Simone Castiello Ciro Indolfi Giovanni Esposito |
| author_sort | Andrea Mariani |
| collection | DOAJ |
| description | Acute coronary syndrome (ACS) is a global health concern that requires rapid and accurate diagnosis for timely intervention and better patient outcomes. With the emergence of Artificial Intelligence (AI), significant advancements have been made in improving diagnostic accuracy, efficiency, and risk stratification in ACS management. This narrative review examines the current landscape of AI applications in ACS diagnosis and risk stratification, emphasizing key methodologies, technical and clinical implementation challenges, and also possible future research directions. Moreover, unlike previous reviews, this paper also focuses on ethical and legal issues and the feasibility of clinical applications. |
| format | Article |
| id | doaj-art-a2e078597354477cb2aa3a1dc1866ce2 |
| institution | OA Journals |
| issn | 2075-1729 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Life |
| spelling | doaj-art-a2e078597354477cb2aa3a1dc1866ce22025-08-20T02:18:09ZengMDPI AGLife2075-17292025-03-0115451510.3390/life15040515Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the LiteratureAndrea Mariani0Carmen Anna Maria Spaccarotella1Francesco Saverio Rea2Anna Franzone3Raffaele Piccolo4Domenico Simone Castiello5Ciro Indolfi6Giovanni Esposito7Department of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyDepartment of Pharmacy, Health and Nutritional Sciences, University of Calabria, Via Pietro Bucci, Arcavacata, 87036 Rende, CS, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, Via Sergio Pansini 5, 80131 Naples, ItalyAcute coronary syndrome (ACS) is a global health concern that requires rapid and accurate diagnosis for timely intervention and better patient outcomes. With the emergence of Artificial Intelligence (AI), significant advancements have been made in improving diagnostic accuracy, efficiency, and risk stratification in ACS management. This narrative review examines the current landscape of AI applications in ACS diagnosis and risk stratification, emphasizing key methodologies, technical and clinical implementation challenges, and also possible future research directions. Moreover, unlike previous reviews, this paper also focuses on ethical and legal issues and the feasibility of clinical applications.https://www.mdpi.com/2075-1729/15/4/515artificial intelligenceacute coronary syndromenarrative reviewmachine learning |
| spellingShingle | Andrea Mariani Carmen Anna Maria Spaccarotella Francesco Saverio Rea Anna Franzone Raffaele Piccolo Domenico Simone Castiello Ciro Indolfi Giovanni Esposito Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature Life artificial intelligence acute coronary syndrome narrative review machine learning |
| title | Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature |
| title_full | Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature |
| title_fullStr | Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature |
| title_full_unstemmed | Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature |
| title_short | Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature |
| title_sort | artificial intelligence and its role in the diagnosis and prediction of adverse events in acute coronary syndrome a narrative review of the literature |
| topic | artificial intelligence acute coronary syndrome narrative review machine learning |
| url | https://www.mdpi.com/2075-1729/15/4/515 |
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