Details

Autor(en) / Beteiligte

• Krittanawong, Chayakrit,

Titel

Artificial intelligence in clinical practice : how AI technologies impact medical research and clinics

Auflage

First edition

Ort / Verlag

Langford Lane, England : Elsevier Inc.,

Erscheinungsjahr

[2024]

Beschreibungen/Notizen

• Includes bibliographical references and index.
• Intro -- Title page -- Table of Contents -- Copyright -- List of contributors -- Foreword -- Chapter 1. Artificial intelligence in primary care -- Abstract -- Introduction -- Potentials -- Limitations and challenges -- Conclusion -- References -- Chapter 2. Artificial intelligence in general internal medicine -- Abstract -- Introduction of artificial intelligence in general medicine -- High-value care -- Perioperative management -- Patient safety and quality issues -- Current challenges preventing artificial intelligence application -- Future directions -- Major takeaway points -- References -- Chapter 3. Artificial intelligence devices and assessment in medical imaging -- Abstract -- Introduction -- Examples of artificial intelligence implementation in medical imaging -- Regulatory framework -- Evaluation framework -- Challenges in artificial intelligence/machine learning device evaluation studies -- Transparency -- Conclusions -- References -- Chapter 4. Artificial intelligence in anatomical pathology -- Abstract -- Introduction -- Overview of digital anatomical pathology workflow -- Applications of artificial intelligence in anatomic pathology -- Conclusions -- References -- Chapter 5. Artificial intelligence in clinical microbiology -- Abstract -- Major takeaways -- References -- Chapter 6. Artificial intelligence on interventional cardiology -- Abstract -- Introduction -- Intravascular imaging (intravascular ultrasound/optical coherence tomography) -- Future directions -- Major takeaway points -- References -- Chapter 7. Artificial intelligence in heart failure and transplant -- Abstract -- Overview of artificial intelligence and machine learning -- Artificial intelligence in heart failure -- Artificial intelligence in cardiac transplantation -- Current limitations of artificial intelligence in heart failure and transplant care.
• Future work -- Major takeaways -- Disclosure -- References -- Chapter 8. Artificial intelligence in hematology -- Abstract -- References -- Chapter 9. Artificial intelligence in oncology -- Abstract -- Introduction -- Artificial intelligence research topics in oncology -- Methodology in artificial intelligence oncology research -- Cancer data: opportunities and challenges -- Conclusion -- References -- Chapter 10. Artificial intelligence in ophthalmology I: retinal diseases -- Abstract -- Artificial intelligence in diabetic retinopathy -- Artificial intelligence in age-related macular degeneration -- Artificial intelligence in retinopathy of prematurity -- Artificial intelligence in retinal vein occlusion -- Challenges and future -- Conclusion -- References -- Chapter 11. Artificial intelligence in ophthalmology II: glaucoma -- Abstract -- Role of artificial intelligence in glaucoma -- Current challenges and limitations -- Future considerations -- Conclusion -- References -- Chapter 12. Artificial intelligence in ophthalmology III: systemic disease prediction -- Abstract -- Introduction -- Artificial intelligence-based ocular image analysis for cardiovascular disease -- Artificial intelligence-based ocular image analysis for renal diseases -- Artificial intelligence-based ocular image analysis for neurological diseases -- Artificial intelligence-based ocular image analysis for other systemic diseases -- Current challenges -- Future directions -- Major takeaway points -- References -- Chapter 13. Artificial intelligence in respiratory medicine -- Abstract -- Introduction discussing the role of artificial intelligence, including a review of the landmark trials, within your field -- Current examples of artificial intelligence implementation in clinical practice (published works to date using artificial intelligence in your area of specialty).
• Current challenges preventing artificial intelligence application -- Future directions with an emphasis on how artificial intelligence can help solve specific problems within your field -- Major takeaways (3-5, one sentence each) -- References -- Chapter 14. Artificial intelligence in critical care -- Abstract -- Introduction -- Artificial intelligence applications in critical care -- Conclusion -- References -- Chapter 15. Artificial intelligence in dermatopathology -- Abstract -- Introduction -- Summary of literature -- Challenges and opportunities -- Future directions -- References -- Chapter 16. Artificial intelligence in infectious diseases -- Abstract -- Introduction -- Artificial intelligence for clinical microbiology -- Artificial intelligence for the clinical diagnosis and management of infected patients -- Challenges for artificial intelligence in infectious diseases -- Conclusion -- References -- Chapter 17. Artificial intelligence in neglected tropical diseases -- Abstract -- Present problems in neglected tropical diseases -- Dilemma in diagnosis of neglected tropical disease -- Applications of artificial intelligence in neglected tropical disease diagnosis -- Challenges of artificial intelligence in neglected tropical disease diagnosis -- Future implications of artificial intelligence in neglected tropical disease diagnosis -- References -- Chapter 18. Artificial intelligence in psychiatry: current practice and major challenges -- Abstract -- Introduction -- Examples of artificial intelligence implementation in clinical practice -- Current limitations and challenges preventing artificial intelligence application -- Future directions -- Conclusion -- References -- Chapter 19. Application of artificial intelligence frameworks in the clinical practice of neurology: recent advances and future directions -- Abstract -- Introduction.
• Current state of artificial intelligence in clinical neurology -- Deployment of artificial intelligence frameworks in healthcare: the ABC cycle -- Conclusions -- Major takeaways -- References -- Chapter 20. Artificial intelligence in rheumatology -- Abstract -- Introduction -- Current examples of artificial intelligence implementation in rheumatology -- Current challenges -- Robust models require sufficient high-quality data -- External validation with independent datasets -- Future direction -- Key messages -- References -- Chapter 21. Artificial intelligence in endocrinology -- Abstract -- Introduction -- Challenges to adoption -- The future of artificial intelligence in endocrinologist daily practice -- Major takeaway points -- Acknowledgments -- Funding -- References -- Chapter 22. Artificial intelligence in sleep medicine -- Abstract -- Introduction -- Current examples of artificial intelligence implementation in clinical practice -- Current challenges -- Future directions -- Major takeaway points -- References -- Chapter 23. Artificial intelligence in nephrology -- Abstract -- Introduction -- Examples of artificial intelligence implementation in nephrology -- Challenges and future directions -- Major takeaway points -- References -- Chapter 24. Artificial intelligence in surgery -- Abstract -- Introduction -- Preoperative planning -- Intraoperative use -- Postoperative care -- Conclusion -- Major takeaway points -- References -- Chapter 25. Artificial intelligence in cardiothoracic surgery: current applications and future perspectives -- Abstract -- Introduction -- Applications of artificial intelligence in cardiothoracic surgery -- Current challenges and future direction of artificial intelligence applications in cardiothoracic surgery -- Conclusion -- Major takeaway points -- Acknowledgments -- References.
• Chapter 26. Artificial intelligence in orthopedics -- Abstract -- Introduction -- Current challenges -- Major takeaway points -- References -- Chapter 27. Artificial intelligence in plastic surgery -- Abstract -- Introduction -- Artificial intelligence implementation in clinical practice -- Current challenges -- Future directions -- Major takeaway points -- References -- Chapter 28. Artificial intelligence in obstetrics and gynecology -- Abstract -- Current applications of artificial intelligence in obstetrics -- Electronic health record analysis for applications of artificial intelligence -- Current applications of artificial intelligence in gynecology -- Future challenges and opportunities for artificial intelligence in obstetrics and gynecology -- References -- Chapter 29. Artificial intelligence in urology -- Abstract -- Introduction (role of artificial intelligence, landmark trials in urology) -- Current examples of artificial intelligence implementation in urology -- Challenges preventing artificial intelligence application -- Future directions -- Major takeaway points -- Abbreviations -- References -- Chapter 30. Artificial intelligence in neurosurgery-a focus on neuro-oncology -- Abstract -- Introduction -- Current examples -- Current challenges preventing artificial intelligence application -- Future directions -- Major takeaway points -- References -- Chapter 31. Artificial intelligence in vascular surgery -- Abstract -- Introduction -- Artificial intelligence applications in vascular surgery -- Artificial intelligence in vascular diagnostics -- Perioperative medicine, risk stratification, and outcome prediction -- Conclusions -- References -- Chapter 32. Artificial intelligence in neonatal and pediatric intensive care units -- Abstract -- Artificial intelligence in pediatrics.
• Current challenges preventing artificial intelligence application.
• 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.
• Description based on print version record.