Intelligence-Based Cardiology and Cardiac Surgery

Artificial Intelligence and Human Cognition in Cardiovascular Medicine

1st Edition - September 1, 2023

Editors: Anthony C Chang, Alfonso Limon, Robert Brisk, Francisco Lopez- Jimenez, Louise Y Sun

Hardback ISBN:

9 7 8 - 0 - 3 2 3 - 9 0 5 3 4 - 3

eBook ISBN:

9 7 8 - 0 - 3 2 3 - 9 0 6 2 9 - 6

Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides an especially timely multidisciplinary and… Read more

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Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides an especially timely multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies. It includes real-life applications in adult and pediatric cardiovascular medicine, spanning the life span from fetus to adult. Led by a senior cardiologist–data scientist and supported by renowned data scientists and cardiac clinicians with an ardent passion for artificial intelligence in cardiovascular medicine, the book provides a clinical interface between the medical and data science domains that is symmetric and realistic.The content consists of basic concepts and applications of artificial intelligence and human cognition in cardiology and cardiac surgery. This portfolio ranges from big data to machine and deep learning, as well as cognitive computing and natural language processing in cardiac disease states such as heart failure, hypertension, and pediatric cardiac care. Artificial intelligence tools are described from the intensive care unit setting to other venues, such as the outpatient clinic, catheterization laboratory, and operating room. Future applications in related areas, such as large language models, extended reality, and digital twins, are also discussed. The book encompasses more than 50 chapters written by cardiologists or cardiac surgeons. Each chapter provides sections on the current state of the art and future directions and concludes with major takeaways. A robust compendium of practical resources, such as a comprehensive glossary, best references, and other resources, is also included.The book narrows the knowledge and expertise chasm between data scientists, cardiologists, and cardiac surgeons, inspires these clinicians to embrace artificial intelligence methodologies, and educates data scientists about the cardiac ecosystem to create a transformational paradigm for cardiovascular healthcare that improves patient outcomes.

Cover image
Title page
Table of Contents
Copyright
Dedication
Contributors
About the editors
Foreword by Eric Topol
Foreword by Ami Bhatt
Preface
Acknowledgments
Section I. Basic concepts of data science and artificial intelligence
Chapter 1. Introduction to artificial intelligence for cardiovascular clinicians
Basic concepts of artificial intelligence
History of artificial intelligence
History of artificial intelligence in medicine
Healthcare data and databases
Machine and deep learning
Assessment of model performance
Fundamental issues in machine and deep learning
Other key concepts and technologies in artificial intelligence
Human cognition and artificial intelligence in cardiology
Current status of AI in medicine and relevance to cardiovascular medicine
Artificial intelligence in cardiovascular medicine
Subsection A. Basic concepts of artificial intelligence in cardiology and cardiac surgery
Chapter 2. Application of artificial intelligence in cardiovascular medicine and cardiac surgery
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 3. Data and databases in cardiovascular medicine and surgery
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 4. Data and databases for pediatric and adult congenital cardiac care
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 5. Cognitive biases and heuristics in human cognition
Introduction
Major Takeaways
Chapter 6. Spectrum bias in algorithms and artificial intelligence
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 7. Medical visual question answering
Introduction
Current state of the art
Future directions
Main takeaways
Subsection B. Artificial intelligence in cardiovascular areas
Chapter 8. Artificial intelligence and the electrocardiogram
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 9. Artificial intelligence in electrophysiology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 10. Artificial intelligence in echocardiography
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 11. Artificial intelligence in cardiac CT
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 12. Artificial intelligence in cardiac MRI
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 13. Artificial intelligence in pediatric and congenital cardiac magnetic resonance imaging
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 14. Artificial intelligence in three-dimensional and fetal echocardiography
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 15. Artificial intelligence in nuclear cardiology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 16. Artificial intelligence and in situ exercise monitoring, modeling, and guidance
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 17. Artificial intelligence in the catheterization laboratory
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 18. Artificial intelligence in the cardiology clinic
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 19. Artificial intelligence in cardiac surgery
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 20. Congenital cardiac surgery and artificial intelligence
Introduction
Current state of the art
Future directions
Major takeaways
Subsection C. Clinical applications of artificial intelligence in cardiovascular medicine
Chapter 21. Artificial intelligence in heart failure
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 22. Big data in cardiovascular population health research
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 23. Intelligence-based cardiovascular disease prevention
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 24. Artificial intelligence in cardiovascular genetics
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 25. Artificial intelligence in congenital heart disease
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 26. Artificial intelligence and cardiovascular disease in women
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 27. Artificial intelligence and COVID-19 in children with heart disease
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 28. Artificial intelligence in cardiac critical care
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 29. Artificial intelligence in cardio-oncology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 30. Artificial intelligence in adult congenital heart disease
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 31. Artificial intelligence for quality improvement
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 32. Clinical safety in cardiology and artificial intelligence
Introduction
Current state of the art
Future directions
Major takeaways
Subsection D. Artificial intelligence and related technologies in cardiovascular medicine
Chapter 33. Data sharing principles
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 34. Natural language processing in cardiovascular medicine
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 35. Artificial intelligence and wearable technology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 36. Digital twin in cardiovascular medicine and surgery
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 37. Artificial intelligence and extended reality in cardiology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 38. Cybersecurity and blockchain in cardiology
Introduction
Current state of the art
Future directions
Major takeaways
Subsection E. Artificial intelligence and special topics in cardiovascular medicine
Chapter 39. Starting an artificial intelligence program in cardiology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 40. Artificial intelligence for cardiac care: a view from the top
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 41. Strategy of artificial intelligence in cardiology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 42. Education of artificial intelligence for cardiovascular clinicians
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 43. Artificial intelligence in cardiology: the trainee perspective
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 44. Artificial intelligence and agile project management
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 45. Synthetic data in cardiovascular health research
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 46. Ethical and legal issues in artificial intelligence-based cardiology
Introduction
Current state of the art
Major takeaways
Chapter 47. Regulatory frameworks for artificial intelligence in cardiovascular medicine and surgery
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 48. Regulatory issues of artificial intelligence in cardiology – international perspective
Introduction
Current state of the art
Future Directions
Major Takeaways
Chapter 49. Industry perspective of artificial intelligence in medicine and surgery
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 50. Entrepreneurship lessons from artificial intelligence in cardiology
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 51. Global cardiac network: an innovative artificial intelligence-enabled learning system
Introduction
Current state of the art
Future directions
Major takeaways
Chapter 52. The future of artificial intelligence in cardiology and cardiac surgery
Introduction
The future of artificial intelligence in cardiology and cardiac surgery
The future of artificial intelligence in cardiovascular medicine—stakeholders
The future of dyads in artificial intelligence in cardiovascular medicine
Major takeaways
Suggested readings
Section III Artificial intelligence in medicine compendium
Appendix. Compendium
Recommended resources
Glossary
Index

Anthony C Chang

Dr. Chang is the founder and medical director of the Medical Intelligence and Innovation Institute (MI3) that is supported by the Sharon Disney Lund Foundation. The institute is dedicated to the introduction and implementation of artificial intelligence in medicine and was the first institute of its kind in a hospital. Dr. Chang intends to build a clinician-computer scientist interface with a nascent society (the Medical Intelligence Society) and is the editor-in-chief of Intelligence-based Medicine, the accompanying journal for his book, Intelligence-Based Medicine: Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare. He is the organizing chair for Artificial Intelligence in Medicine (AIMed) meetings around the world, the largest and most comprehensive clinician-led meetings that focus on applications of artificial intelligence in medicine and the dean of the nascent American Board of Artificial Intelligence in Medicine (ABAIM). He is also the founding president of the Medical Intelligence Society (MIS).

Affiliations and expertise

Sharon Disney Lund Medical Intelligence, Information, Investigation, and Innovation Institute (Mi4), Children’s Health of Orange County, Orange, CA, USA; Heart Failure Program, Heart Institute, Children’s Health of Orange County, Orange, CA, USA; Chapman University, Orange, CA, USA

Alfonso Limon

Alfonso Limon, Ph.D., is a principal at Oneirix, a consulting company developing market-leading technologies in computational intelligence for med-tech. Before joining Oneirix, Dr. Limon served as Director of Research at Intersection Medical, leading the development of algorithms for decision support systems to manage congestive heart failure. Before his work in industry, Dr. Limon was a Visiting Professor of Mathematics at Pomona College and a post-doctoral fellow at Harvey Mudd College in the math department and holds several impedance spectroscopy patents. Alfonso is part of the American Board of Artificial Intelligence in Medicine, an Associate Editor of Intelligence-Based Medicine, and the Computational Science Research Center Board Chair at SDSU.

Affiliations and expertise

Principal, Oneirix Labs, USA

Francisco Lopez- Jimenez

Dr. Lopez-Jimenez is a Professor of Medicine at Mayo Clinic College of Medicine, the Chair of the Division of Preventive Cardiology at Mayo Clinic and Co-Director of Artificial Intelligence in Cardiology in the Department of Cardiovascular Medicine. He is the Editor-In-Chief of Mayo Clinic Proceedings: Digital Health and the Co-Chair for the Advanced Healthcare Analytics workgroup, American College of Cardiology. Dr. Lopez-Jimenez did his cardiology fellowship at Mount Sinai Medical Center in Miami, Florida and at Brigham and Women’s Hospital, Harvard Medical School. He holds a Master of Science degree from Harvard School of Public Health and a MBA degree from Augsburg University. Dr. Lopez-Jimenez has published more than 365 scientific publications and his scientific work has been cited more than 17,000 times.

Affiliations and expertise

Professor of Medicine, Mayo Clinic College of Medicine, MN, USA Chair of the Division of Preventive Cardiology, Mayo Clinic, MN, USA Co-Director of Artificial Intelligence in Cardiology in the Department of Cardiovascular Medicine, USA

Louise Y Sun

Dr. Sun is Professor and Chief of Cardiothoracic Anesthesiology at Stanford. Her areas of clinical focus are hemodynamic monitoring and heart failure. Her methodologic areas of focus are the conduct of population-based cohort studies, predictive analytics, sex and gender epidemiology, patient engagement, data warehousing, and applications development. Her patient-centered research program leverages big data and digital technology to bridge key gaps in the delivery of care and outcomes for patients with heart failure and those undergoing cardiovascular interventions, through personalized risk stratification and characterizing long-term, patient-defined outcomes. She specializes in rapidly developing and deploying data-driven solutions to enhance clinical operations and patient care, and collaborates with policy makers to evaluate models of cardiac healthcare delivery. Dr. Sun sits on a number of editorial boards and scientific review committees internationally. She has authored over 100 peer-reviewed publications, many in leading journals including JAMA, JAMA Cardiology, JAMA Internal Medicine, Circulation, JACC, and Diabetes Care.

Affiliations and expertise

Professor and Chief of Cardiothoracic Anesthesiologiy, Stanford University School of Medicine, Stanford, CA, USA