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Nedadur R, Bhatt N, Liu T, Chu MWA, McCarthy PM, Kline A. The Emerging and Important Role of Artificial Intelligence in Cardiac Surgery. Can J Cardiol 2024; 40:1865-1879. [PMID: 39098601 DOI: 10.1016/j.cjca.2024.07.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 07/29/2024] [Accepted: 07/29/2024] [Indexed: 08/06/2024] Open
Abstract
Artificial Intelligence (AI) has greatly affected our everyday lives and holds great promise to change the landscape of medicine. AI is particularly positioned to improve care for the increasingly complex patients undergoing cardiac surgery using the immense amount of data generated in the course of their care. When deployed, AI can be used to analyze this information at the patient's bedside more expediently and accurately, all while providing new insights. This review summarizes the current applications of AI in cardiac surgery from the vantage point of a patient's journey. Applications of AI include preoperative risk assessment, intraoperative planning, postoperative patient care, and outpatient telemonitoring, encompassing the spectrum of cardiac surgical care. Offloading of administrative processes and enhanced experience with information gathering also represent a unique and under-represented avenue for future use of AI. As clinicians, understanding the nomenclature and applications of AI is important to contextualize issues, to ensure problem-driven solutions, and for clinical benefit. Precision medicine, and thus clinically relevant AI, remains dependent on data curation and warehousing to gather insights from large multicentre repositories while treating privacy with the utmost importance. AI tasks should not be siloed but rather holistically integrated into clinical workflow to retain context and relevance. As cardiac surgeons, AI allows us to look forward to a bright future of more efficient use of our clinical expertise toward high-level decision making and technical prowess.
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Affiliation(s)
- Rashmi Nedadur
- Feinberg School of Medicine, Division of Cardiac Surgery, Northwestern University, Chicago, Illinois, USA; Center for Artificial Intelligence, Bluhm Cardiovascular Institute, Northwestern Medicine, Chicago, Illinois, USA.
| | - Nitish Bhatt
- Peter Munk Cardiac Center, Toronto General Hospital, Toronto, Ontario, Canada
| | - Tom Liu
- Feinberg School of Medicine, Division of Cardiac Surgery, Northwestern University, Chicago, Illinois, USA; Center for Artificial Intelligence, Bluhm Cardiovascular Institute, Northwestern Medicine, Chicago, Illinois, USA
| | | | - Patrick M McCarthy
- Feinberg School of Medicine, Division of Cardiac Surgery, Northwestern University, Chicago, Illinois, USA; Center for Artificial Intelligence, Bluhm Cardiovascular Institute, Northwestern Medicine, Chicago, Illinois, USA
| | - Adrienne Kline
- Feinberg School of Medicine, Division of Cardiac Surgery, Northwestern University, Chicago, Illinois, USA; Center for Artificial Intelligence, Bluhm Cardiovascular Institute, Northwestern Medicine, Chicago, Illinois, USA
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Pozza A, Zanella L, Castaldi B, Di Salvo G. How Will Artificial Intelligence Shape the Future of Decision-Making in Congenital Heart Disease? J Clin Med 2024; 13:2996. [PMID: 38792537 PMCID: PMC11122569 DOI: 10.3390/jcm13102996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Improvements in medical technology have significantly changed the management of congenital heart disease (CHD), offering novel tools to predict outcomes and personalize follow-up care. By using sophisticated imaging modalities, computational models and machine learning algorithms, clinicians can experiment with unprecedented insights into the complex anatomy and physiology of CHD. These tools enable early identification of high-risk patients, thus allowing timely, tailored interventions and improved outcomes. Additionally, the integration of genetic testing offers valuable prognostic information, helping in risk stratification and treatment optimisation. The birth of telemedicine platforms and remote monitoring devices facilitates customised follow-up care, enhancing patient engagement and reducing healthcare disparities. Taking into consideration challenges and ethical issues, clinicians can make the most of the full potential of artificial intelligence (AI) to further refine prognostic models, personalize care and improve long-term outcomes for patients with CHD. This narrative review aims to provide a comprehensive illustration of how AI has been implemented as a new technological method for enhancing the management of CHD.
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Affiliation(s)
- Alice Pozza
- Paediatric Cardiology Unit, Department of Women’s and Children’s Health, University of Padua, 35122 Padova, Italy; (A.P.)
| | - Luca Zanella
- Heart Surgery, Department of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy
- Cardiac Surgery Unit, Department of Cardiac-Thoracic-Vascular Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Biagio Castaldi
- Paediatric Cardiology Unit, Department of Women’s and Children’s Health, University of Padua, 35122 Padova, Italy; (A.P.)
| | - Giovanni Di Salvo
- Paediatric Cardiology Unit, Department of Women’s and Children’s Health, University of Padua, 35122 Padova, Italy; (A.P.)
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Dallaire F, Grewal J, Mawad W, Wald RM. Challenges and Opportunities for Patients With Tetralogy of Fallot Across the Lifespan. CJC PEDIATRIC AND CONGENITAL HEART DISEASE 2023; 2:253-255. [PMID: 38161677 PMCID: PMC10755820 DOI: 10.1016/j.cjcpc.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 11/05/2023] [Indexed: 01/03/2024]
Affiliation(s)
- Frédéric Dallaire
- Department of Pediatrics, Université de Sherbrooke, and Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
| | - Jasmine Grewal
- Division of Cardiology, St Paul’s Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Wadi Mawad
- Division of Cardiology, Montreal Children’s Hospital, McGill University Health Center, Montreal, Québec, Canada
| | - Rachel M. Wald
- University Health Network, Peter Munk Cardiac Centre, Toronto Adult Congenital Heart Disease Program, University of Toronto, Toronto, Ontario, Canada
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