Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN.
This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine.
1. Artificial Intelligence in Clinical Practice - p. iii 2. Cover - p. iii 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. v 6. List of contributors - p. xv 7. Foreword - p. xxiii 8. Chapter 1 Artificial intelligence in primary care - p. 1 9. Chapter 2 Artificial intelligence in general internal medicine - p. 15 10. Chapter 3 Artificial intelligence devices and assessment in medical imaging - p. 25 11. Chapter 4 Artificial intelligence in anatomical pathology - p. 35 12. Chapter 5 Artificial intelligence in clinical microbiology - p. 47 13. Chapter 6 Artificial intelligence on interventional cardiology - p. 51 14. Chapter 7 Artificial intelligence in heart failure and transplant - p. 65 15. Chapter 8 Artificial intelligence in hematology - p. 95 16. Chapter 9 Artificial intelligence in oncology - p. 101 17. Chapter 10 Artificial intelligence in ophthalmology I: retinal diseases - p. 107 18. Chapter 11 Artificial intelligence in ophthalmology II: glaucoma - p. 113 19. Chapter 12 Artificial intelligence in ophthalmology III: systemic disease prediction - p. 119 20. Chapter 13 Artificial intelligence in respiratory medicine - p. 127 21. Chapter 14 Artificial intelligence in critical care - p. 137 22. Chapter 15 Artificial intelligence in dermatopathology - p. 145 23. Chapter 16 Artificial intelligence in infectious diseases - p. 151 24. Chapter 17 Artificial intelligence in neglected tropical diseases - p. 155 25. Chapter 18 Artificial intelligence in psychiatry: current practice and major challenges - p. 163 26. Chapter 19 Application of artificial intelligence frameworks in the clinical practice of neurology: recent advances and future directions - p. 169 27. Chapter 20 Artificial intelligence in rheumatology - p. 177 28. Chapter 21 Artificial intelligence in endocrinology - p. 187 29. Chapter 22 Artificial intelligence in sleep medicine - p. 195 30. Chapter 23 Artificial intelligence in nephrology - p. 201 31. Chapter 24 Artificial intelligence in surgery - p. 211 32. Chapter 25 Artificial intelligence in cardiothoracic surgery: current applications and future perspectives - p. 217 33. Chapter 26 Artificial intelligence in orthopedics - p. 235 34. Chapter 27 Artificial intelligence in plastic surgery - p. 245 35. Chapter 28 Artificial intelligence in obstetrics and gynecology - p. 251 36. Chapter 29 Artificial intelligence in urology - p. 259 37. Chapter 30 Artificial intelligence in neurosurgery—a focus on neuro-oncology - p. 267 38. Chapter 31 Artificial intelligence in vascular surgery - p. 271 39. Chapter 32 Artificial intelligence in neonatal and pediatric intensive care units - p. 275 40. Chapter 33 Artificial intelligence in pediatrics - p. 285 41. Chapter 34 Artificial intelligence in pediatric congenital and acquired heart disease - p. 297 42. Chapter 35 Artificial intelligence in anesthesiology - p. 307 43. Chapter 36 Artificial intelligence in emergency medicine - p. 315 44. Chapter 37 Artificial intelligence in allergy and immunology - p. 319 45. Chapter 38 Artificial intelligence in medical genetics - p. 329 46. Chapter 39 Artificial intelligence in healthcare: a perspective from Google - p. 341 47. Chapter 40 Artificial intelligence drives the digital transformation of pharma - p. 345 48. Chapter 41 Artificial intelligence in regulatory decision-making for drug and biological products - p. 373 49. Chapter 42 Machine learning applications in toxicology - p. 377 50. Chapter 43 Artificial intelligence in adverse drug events - p. 383 51. Chapter 44 Artificial intelligence in mass spectrometry-based proteomics - p. 389 52. Chapter 45 Artificial intelligence and global health - p. 395 53. Chapter 46 Legal aspects of artificial intelligence in medical practice - p. 401 54. Chapter 47 Socioeconomic bias in applying artificial intelligence models to health care - p. 413 55. Chapter 48 Artificial intelligence in dermatology - p. 437 56. Chapter 49 Artificial intelligence in gastroenterology and hepatology - p. 443 57. Chapter 50 Artificial intelligence in nutrition research - p. 465 58. Chapter 51 Artificial intelligence in cardiac electrophysiology - p. 475 59. Index - p. 497
Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN.
This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine.
1. Artificial Intelligence in Clinical Practice - p. iii 2. Cover - p. iii 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. v 6. List of contributors - p. xv 7. Foreword - p. xxiii 8. Chapter 1 Artificial intelligence in primary care - p. 1 9. Chapter 2 Artificial intelligence in general internal medicine - p. 15 10. Chapter 3 Artificial intelligence devices and assessment in medical imaging - p. 25 11. Chapter 4 Artificial intelligence in anatomical pathology - p. 35 12. Chapter 5 Artificial intelligence in clinical microbiology - p. 47 13. Chapter 6 Artificial intelligence on interventional cardiology - p. 51 14. Chapter 7 Artificial intelligence in heart failure and transplant - p. 65 15. Chapter 8 Artificial intelligence in hematology - p. 95 16. Chapter 9 Artificial intelligence in oncology - p. 101 17. Chapter 10 Artificial intelligence in ophthalmology I: retinal diseases - p. 107 18. Chapter 11 Artificial intelligence in ophthalmology II: glaucoma - p. 113 19. Chapter 12 Artificial intelligence in ophthalmology III: systemic disease prediction - p. 119 20. Chapter 13 Artificial intelligence in respiratory medicine - p. 127 21. Chapter 14 Artificial intelligence in critical care - p. 137 22. Chapter 15 Artificial intelligence in dermatopathology - p. 145 23. Chapter 16 Artificial intelligence in infectious diseases - p. 151 24. Chapter 17 Artificial intelligence in neglected tropical diseases - p. 155 25. Chapter 18 Artificial intelligence in psychiatry: current practice and major challenges - p. 163 26. Chapter 19 Application of artificial intelligence frameworks in the clinical practice of neurology: recent advances and future directions - p. 169 27. Chapter 20 Artificial intelligence in rheumatology - p. 177 28. Chapter 21 Artificial intelligence in endocrinology - p. 187 29. Chapter 22 Artificial intelligence in sleep medicine - p. 195 30. Chapter 23 Artificial intelligence in nephrology - p. 201 31. Chapter 24 Artificial intelligence in surgery - p. 211 32. Chapter 25 Artificial intelligence in cardiothoracic surgery: current applications and future perspectives - p. 217 33. Chapter 26 Artificial intelligence in orthopedics - p. 235 34. Chapter 27 Artificial intelligence in plastic surgery - p. 245 35. Chapter 28 Artificial intelligence in obstetrics and gynecology - p. 251 36. Chapter 29 Artificial intelligence in urology - p. 259 37. Chapter 30 Artificial intelligence in neurosurgery—a focus on neuro-oncology - p. 267 38. Chapter 31 Artificial intelligence in vascular surgery - p. 271 39. Chapter 32 Artificial intelligence in neonatal and pediatric intensive care units - p. 275 40. Chapter 33 Artificial intelligence in pediatrics - p. 285 41. Chapter 34 Artificial intelligence in pediatric congenital and acquired heart disease - p. 297 42. Chapter 35 Artificial intelligence in anesthesiology - p. 307 43. Chapter 36 Artificial intelligence in emergency medicine - p. 315 44. Chapter 37 Artificial intelligence in allergy and immunology - p. 319 45. Chapter 38 Artificial intelligence in medical genetics - p. 329 46. Chapter 39 Artificial intelligence in healthcare: a perspective from Google - p. 341 47. Chapter 40 Artificial intelligence drives the digital transformation of pharma - p. 345 48. Chapter 41 Artificial intelligence in regulatory decision-making for drug and biological products - p. 373 49. Chapter 42 Machine learning applications in toxicology - p. 377 50. Chapter 43 Artificial intelligence in adverse drug events - p. 383 51. Chapter 44 Artificial intelligence in mass spectrometry-based proteomics - p. 389 52. Chapter 45 Artificial intelligence and global health - p. 395 53. Chapter 46 Legal aspects of artificial intelligence in medical practice - p. 401 54. Chapter 47 Socioeconomic bias in applying artificial intelligence models to health care - p. 413 55. Chapter 48 Artificial intelligence in dermatology - p. 437 56. Chapter 49 Artificial intelligence in gastroenterology and hepatology - p. 443 57. Chapter 50 Artificial intelligence in nutrition research - p. 465 58. Chapter 51 Artificial intelligence in cardiac electrophysiology - p. 475 59. Index - p. 497
