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.
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Table of Contents
I. INTRODUCTION TO ARTIFICIAL INTELLIGENCE 1. Basic Concepts of Artificial Intelligence 2. History of Artificial Intelligence 3. History of Artificial Intelligence in Medicine II. DATA SCIENCE AND ARTIFICIAL INTELLIGENCE IN THE CURRENT ERA 4. Health Care Data and Databases 5. Machine and Deep Learning 6. Other Key Concepts in Artificial Intelligence III. THE CURRENT ERA OF ARTIFICIAL INTELLIGENCE IN MEDICINE 7. Clinician Cognition & Artificial Intelligence in MedicineAuthors
Anthony C Chang 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. 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). Alfonso Limon Principal, Oneirix Labs, USA. 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. Robert Brisk Francisco Lopez- Jimenez Professor of Medicine, Mayo Clinic College of Medicine, MN, USAChair of the Division of Preventive Cardiology, Mayo Clinic, MN, USA
Co-Director of Artificial Intelligence in Cardiology in the Department of Cardiovascular Medicine, USA. 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. Louise Y Sun Professor and Chief of Cardiothoracic Anesthesiologiy, Stanford University School of Medicine, Stanford, CA, USA. 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.
