Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides a comprehensive survey of artificial intelligence concepts and methodologies with real-life applications in cardiovascular medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and data science domains. The book's content consists of basic concepts of artificial intelligence and human cognition applications in cardiology and cardiac surgery. This portfolio ranges from big data, machine and deep learning, cognitive computing and natural language processing in cardiac disease states such as heart failure, hypertension and pediatric heart care.
The book narrows the knowledge and expertise chasm between the data scientists, cardiologists and cardiac surgeons, inspiring clinicians to embrace artificial intelligence methodologies, educate data scientists about the medical ecosystem, and create a transformational paradigm for healthcare and medicine.
1. Chapter 1 : Introduction to artificial intelligence for cardiovascular clinicians - p. Page xvi 2. Chapter 2 : Application of artificial intelligence in cardiovascular medicine and cardiac surgery - p. Page 115 3. Chapter 3 : Data and databases in cardiovascular medicine and surgery - p. Page 128 4. Chapter 4 : Data and databases for pediatric and adult congenital cardiac care - p. Page 133 5. Chapter 5 : Cognitive biases and heuristics in human cognition - p. Page 140 6. Chapter 6 : Spectrum bias in algorithms and artificial intelligence - p. Page 150 7. Chapter 7 : Medical visual question answering - p. Page 156 8. Chapter 8 : Artificial intelligence and the electrocardiogram - p. Page 161 9. Chapter 9 : Artificial intelligence in electrophysiology - p. Page 168 10. Chapter 10 : Artificial intelligence in echocardiography - p. Page 176 11. Chapter 11 : Artificial intelligence in cardiac CT - p. Page 183 12. Chapter 12 : Artificial intelligence in cardiac MRI - p. Page 188 13. Chapter 13 : Artificial intelligence in pediatric and congenital cardiac magnetic resonance imaging - p. Page 196 14. Chapter 14 : Artificial intelligence in three-dimensional and fetal echocardiography - p. Page 206 15. Chapter 15 : Artificial intelligence in nuclear cardiology - p. Page 214 16. Chapter 16 : Artificial intelligence and in situ exercise monitoring, modeling, and guidance - p. Page 223 17. Chapter 17 : Artificial intelligence in the catheterization laboratory - p. Page 229 18. Chapter 18 : Artificial intelligence in the cardiology clinic - p. Page 234 19. Chapter 19 : Artificial intelligence in cardiac surgery - p. Page 241 20. Chapter 20 : Congenital cardiac surgery and artificial intelligence - p. Page 246 21. Chapter 21 : Artificial intelligence in heart failure - p. Page 251 22. Chapter 22 : Big data in cardiovascular population health research - p. Page 259 23. Chapter 23 : Intelligence-based cardiovascular disease prevention - p. Page 264 24. Chapter 24 : Artificial intelligence in cardiovascular genetics - p. Page 268 25. Chapter 25 : Artificial intelligence in congenital heart disease - p. Page 276 26. Chapter 26 : Artificial intelligence and cardiovascular disease in women - p. Page 283 27. Chapter 27 : Artificial intelligence and COVID-19 in children with heart disease - p. Page 290 28. Chapter 28 : Artificial intelligence in cardiac critical care - p. Page 300 29. Chapter 29 : Artificial intelligence in cardio-oncology - p. Page 306 30. Chapter 30 : Artificial intelligence in adult congenital heart disease - p. Page 312 31. Chapter 31 : Artificial intelligence for quality improvement - p. Page 319 32. Chapter 32 : Clinical safety in cardiology and artificial intelligence - p. Page 325 33. Chapter 33 : Data sharing principles - p. Page 330 34. Chapter 34 : Natural language processing in cardiovascular medicine - p. Page 341 35. Chapter 35 : Artificial intelligence and wearable technology - p. Page 349 36. Chapter 36 : Digital twin in cardiovascular medicine and surgery - p. Page 355 37. Chapter 37 : Artificial intelligence and extended reality in cardiology - p. Page 360 38. Chapter 38 : Cybersecurity and blockchain in cardiology - p. Page 366 39. Chapter 39 : Starting an artificial intelligence program in cardiology - p. Page 370 40. Chapter 40 : Artificial intelligence for cardiac care: a view from the top - p. Page 377 41. Chapter 41 : Strategy of artificial intelligence in cardiology - p. Page 384 42. Chapter 42 : Education of artificial intelligence for cardiovascular clinicians - p. Page 391 43. Chapter 43 : Artificial intelligence in cardiology: the trainee perspective - p. Page 395 44. Chapter 44 : Artificial intelligence and agile project management - p. Page 399 45. Chapter 45 : Synthetic data in cardiovascular health research - p. Page 405 46. Chapter 46 : Ethical and legal issues in artificial intelligence-based cardiology - p. Page 412 47. Chapter 47 : Regulatory frameworks for artificial intelligence in cardiovascular medicine and surgery - p. Page 418 48. Chapter 48 : Regulatory issues of artificial intelligence in cardiology – international perspective - p. Page 426 49. Chapter 49 : Industry perspective of artificial intelligence in medicine and surgery - p. Page 430 50. Chapter 50 : Entrepreneurship lessons from artificial intelligence in cardiology - p. Page 433 51. Chapter 51 : Global cardiac network: an innovative artificial intelligence-enabled learning system - p. Page 439 52. Chapter 52 : The future of artificial intelligence in cardiology and cardiac surgery - p. Page 447 53. Appendix : Compendium - p. Page 455 54. Recommended resources - p. Page 471 55. Glossary - p. Page 477 56. Index - p. Page 501
Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides a comprehensive survey of artificial intelligence concepts and methodologies with real-life applications in cardiovascular medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and data science domains. The book's content consists of basic concepts of artificial intelligence and human cognition applications in cardiology and cardiac surgery. This portfolio ranges from big data, machine and deep learning, cognitive computing and natural language processing in cardiac disease states such as heart failure, hypertension and pediatric heart care.
The book narrows the knowledge and expertise chasm between the data scientists, cardiologists and cardiac surgeons, inspiring clinicians to embrace artificial intelligence methodologies, educate data scientists about the medical ecosystem, and create a transformational paradigm for healthcare and medicine.
1. Chapter 1 : Introduction to artificial intelligence for cardiovascular clinicians - p. Page xvi 2. Chapter 2 : Application of artificial intelligence in cardiovascular medicine and cardiac surgery - p. Page 115 3. Chapter 3 : Data and databases in cardiovascular medicine and surgery - p. Page 128 4. Chapter 4 : Data and databases for pediatric and adult congenital cardiac care - p. Page 133 5. Chapter 5 : Cognitive biases and heuristics in human cognition - p. Page 140 6. Chapter 6 : Spectrum bias in algorithms and artificial intelligence - p. Page 150 7. Chapter 7 : Medical visual question answering - p. Page 156 8. Chapter 8 : Artificial intelligence and the electrocardiogram - p. Page 161 9. Chapter 9 : Artificial intelligence in electrophysiology - p. Page 168 10. Chapter 10 : Artificial intelligence in echocardiography - p. Page 176 11. Chapter 11 : Artificial intelligence in cardiac CT - p. Page 183 12. Chapter 12 : Artificial intelligence in cardiac MRI - p. Page 188 13. Chapter 13 : Artificial intelligence in pediatric and congenital cardiac magnetic resonance imaging - p. Page 196 14. Chapter 14 : Artificial intelligence in three-dimensional and fetal echocardiography - p. Page 206 15. Chapter 15 : Artificial intelligence in nuclear cardiology - p. Page 214 16. Chapter 16 : Artificial intelligence and in situ exercise monitoring, modeling, and guidance - p. Page 223 17. Chapter 17 : Artificial intelligence in the catheterization laboratory - p. Page 229 18. Chapter 18 : Artificial intelligence in the cardiology clinic - p. Page 234 19. Chapter 19 : Artificial intelligence in cardiac surgery - p. Page 241 20. Chapter 20 : Congenital cardiac surgery and artificial intelligence - p. Page 246 21. Chapter 21 : Artificial intelligence in heart failure - p. Page 251 22. Chapter 22 : Big data in cardiovascular population health research - p. Page 259 23. Chapter 23 : Intelligence-based cardiovascular disease prevention - p. Page 264 24. Chapter 24 : Artificial intelligence in cardiovascular genetics - p. Page 268 25. Chapter 25 : Artificial intelligence in congenital heart disease - p. Page 276 26. Chapter 26 : Artificial intelligence and cardiovascular disease in women - p. Page 283 27. Chapter 27 : Artificial intelligence and COVID-19 in children with heart disease - p. Page 290 28. Chapter 28 : Artificial intelligence in cardiac critical care - p. Page 300 29. Chapter 29 : Artificial intelligence in cardio-oncology - p. Page 306 30. Chapter 30 : Artificial intelligence in adult congenital heart disease - p. Page 312 31. Chapter 31 : Artificial intelligence for quality improvement - p. Page 319 32. Chapter 32 : Clinical safety in cardiology and artificial intelligence - p. Page 325 33. Chapter 33 : Data sharing principles - p. Page 330 34. Chapter 34 : Natural language processing in cardiovascular medicine - p. Page 341 35. Chapter 35 : Artificial intelligence and wearable technology - p. Page 349 36. Chapter 36 : Digital twin in cardiovascular medicine and surgery - p. Page 355 37. Chapter 37 : Artificial intelligence and extended reality in cardiology - p. Page 360 38. Chapter 38 : Cybersecurity and blockchain in cardiology - p. Page 366 39. Chapter 39 : Starting an artificial intelligence program in cardiology - p. Page 370 40. Chapter 40 : Artificial intelligence for cardiac care: a view from the top - p. Page 377 41. Chapter 41 : Strategy of artificial intelligence in cardiology - p. Page 384 42. Chapter 42 : Education of artificial intelligence for cardiovascular clinicians - p. Page 391 43. Chapter 43 : Artificial intelligence in cardiology: the trainee perspective - p. Page 395 44. Chapter 44 : Artificial intelligence and agile project management - p. Page 399 45. Chapter 45 : Synthetic data in cardiovascular health research - p. Page 405 46. Chapter 46 : Ethical and legal issues in artificial intelligence-based cardiology - p. Page 412 47. Chapter 47 : Regulatory frameworks for artificial intelligence in cardiovascular medicine and surgery - p. Page 418 48. Chapter 48 : Regulatory issues of artificial intelligence in cardiology – international perspective - p. Page 426 49. Chapter 49 : Industry perspective of artificial intelligence in medicine and surgery - p. Page 430 50. Chapter 50 : Entrepreneurship lessons from artificial intelligence in cardiology - p. Page 433 51. Chapter 51 : Global cardiac network: an innovative artificial intelligence-enabled learning system - p. Page 439 52. Chapter 52 : The future of artificial intelligence in cardiology and cardiac surgery - p. Page 447 53. Appendix : Compendium - p. Page 455 54. Recommended resources - p. Page 471 55. Glossary - p. Page 477 56. Index - p. Page 501
