Intelligence-Based Cardiology and Cardiac Surgery
Artificial Intelligence and Human Cognition in Cardiovascular Medicine
- 1st Edition - September 1, 2023
- Editor: Alfonso Limon
- Language: English
- 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 compre… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteIntelligence-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.
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.
- Covers a wide range of relevant topics from real-world data, large language models, and supervised machine learning to deep reinforcement and federated learning
- Presents artificial intelligence concepts and their applications in many areas in an easy-to-understand format accessible to clinicians and data scientists
- Discusses using artificial intelligence and related technologies with cardiology and cardiac surgery in a myriad of venues and situations
- Delineates the necessary elements for successfully implementing artificial intelligence in cardiovascular medicine for improved patient outcomes
- Presents the regulatory, ethical, legal, and financial issues embedded in artificial intelligence applications in cardiology
Cardiologists (adult and pediatric), Cardiac surgeons (adult and pediatric), Cardiac anesthesiologists, Cardiac intensivists, Trainees in these fields (adult and pediatric), Nurses and technologists in these fields, Health executives, Data scientists (primary), Inventors, Entrepreneurs
- 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
- No. of pages: 540
- Language: English
- Edition: 1
- Published: September 1, 2023
- Imprint: Academic Press
- Hardback ISBN: 9780323905343
- eBook ISBN: 9780323906296
AL
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, USARead Intelligence-Based Cardiology and Cardiac Surgery on ScienceDirect