Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future
<b>Background:</b> Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI’s application...
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| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Clinics and Practice |
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| Online Access: | https://www.mdpi.com/2039-7283/15/1/17 |
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| author | Vasileios Leivaditis Eleftherios Beltsios Athanasios Papatriantafyllou Konstantinos Grapatsas Francesk Mulita Nikolaos Kontodimopoulos Nikolaos G. Baikoussis Levan Tchabashvili Konstantinos Tasios Ioannis Maroulis Manfred Dahm Efstratios Koletsis |
| author_facet | Vasileios Leivaditis Eleftherios Beltsios Athanasios Papatriantafyllou Konstantinos Grapatsas Francesk Mulita Nikolaos Kontodimopoulos Nikolaos G. Baikoussis Levan Tchabashvili Konstantinos Tasios Ioannis Maroulis Manfred Dahm Efstratios Koletsis |
| author_sort | Vasileios Leivaditis |
| collection | DOAJ |
| description | <b>Background:</b> Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI’s applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. <b>Methods:</b> A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. <b>Results:</b> A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. <b>Conclusions:</b> AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery. |
| format | Article |
| id | doaj-art-7bf33720fde64aed8aec2e9f163a4ab5 |
| institution | Kabale University |
| issn | 2039-7283 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Clinics and Practice |
| spelling | doaj-art-7bf33720fde64aed8aec2e9f163a4ab52025-01-24T13:27:43ZengMDPI AGClinics and Practice2039-72832025-01-011511710.3390/clinpract15010017Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the FutureVasileios Leivaditis0Eleftherios Beltsios1Athanasios Papatriantafyllou2Konstantinos Grapatsas3Francesk Mulita4Nikolaos Kontodimopoulos5Nikolaos G. Baikoussis6Levan Tchabashvili7Konstantinos Tasios8Ioannis Maroulis9Manfred Dahm10Efstratios Koletsis11Department of Cardiothoracic and Vascular Surgery, WestpfalzKlinikum, 67655 Kaiserslautern, GermanyDepartment of Anesthesiology and Intensive Care, Hannover Medical School, 30625 Hannover, GermanyDepartment of Cardiothoracic and Vascular Surgery, WestpfalzKlinikum, 67655 Kaiserslautern, GermanyDepartment of Thoracic Surgery and Thoracic Endoscopy, Ruhrlandklinik, West German Lung Center, University Hospital Essen, University Duisburg-Essen, 45141 Essen, GermanyDepartment of General Surgery, General University Hospital of Patras, 26504 Patras, GreeceDepartment of Economics and Sustainable Development, Harokopio University, 17778 Athens, GreeceDepartment of Cardiac Surgery, Ippokrateio General Hospital of Athens, 11527 Athens, GreeceDepartment of General Surgery, General University Hospital of Patras, 26504 Patras, GreeceDepartment of General Surgery, General University Hospital of Patras, 26504 Patras, GreeceDepartment of General Surgery, General University Hospital of Patras, 26504 Patras, GreeceDepartment of Cardiothoracic and Vascular Surgery, WestpfalzKlinikum, 67655 Kaiserslautern, GermanyDepartment of Cardiothoracic Surgery, General University Hospital of Patras, 26504 Patras, Greece<b>Background:</b> Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI’s applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. <b>Methods:</b> A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. <b>Results:</b> A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. <b>Conclusions:</b> AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery.https://www.mdpi.com/2039-7283/15/1/17artificial intelligencecardiac surgerymachine learningrobotic-assisted surgeryrisk stratificationaugmented cognition |
| spellingShingle | Vasileios Leivaditis Eleftherios Beltsios Athanasios Papatriantafyllou Konstantinos Grapatsas Francesk Mulita Nikolaos Kontodimopoulos Nikolaos G. Baikoussis Levan Tchabashvili Konstantinos Tasios Ioannis Maroulis Manfred Dahm Efstratios Koletsis Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future Clinics and Practice artificial intelligence cardiac surgery machine learning robotic-assisted surgery risk stratification augmented cognition |
| title | Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future |
| title_full | Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future |
| title_fullStr | Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future |
| title_full_unstemmed | Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future |
| title_short | Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future |
| title_sort | artificial intelligence in cardiac surgery transforming outcomes and shaping the future |
| topic | artificial intelligence cardiac surgery machine learning robotic-assisted surgery risk stratification augmented cognition |
| url | https://www.mdpi.com/2039-7283/15/1/17 |
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