This book provides an introduction into the field of digital medicine, its wide spectrum of current clinical applications, and the future practice of medicine. With "digital health" and "digital medicine" at its core, it focuses on the combination of therapeutics with modern hard- and software solutions, including artificial intelligence and advanced diagnostic technologies such as augmented imaging and ingestible or wearable (nano)sensors, to provide best patient care. In the four parts of this book, experts in the field have authored use cases and guiding principles on the visualization of patient data analytics and clinical decision support tools, including robotic-guided interventions, as well as nursing research along with palliative and inpatient care. The book also provides examples of "digital medicine" from almost all clinical disciplines together with technical and e-learning solutions.
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This book provides an introduction into the field of digital medicine, its wide spectrum of current clinical applications, and the future practice of medicine. The book also provides examples of "digital medicine" from almost all clinical disciplines together with technical and e-learning solutions.
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1. Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge 2. Data Access and Use 3. Data Integration 4. Data analysis in Genomic Medicine: Status, Challenges and Developments 5. Ethical Aspects of mHealth Technologies: Challenges and Opportunities 6. i-Learning the Next Generation e-Learning 7. Data-Driven Nursing Research: An Overview of Underlying Concepts and Enablers 8. Designing the Hospital of the Future: A Framework to Guide Digital Innovation 9. Combining Digital Medicine, Innovative Geospatial and Environmental Data in Environmental Health Sciences to Create Sustainable Health 10. Digitalization and (Nano)Robotics in Nanomedicine 11. Neural Networks in Molecular Imaging: Theory and Applications 12. Precision Oncology: Molecular Diversification of Tumor Patients 13. Digital Applications in Precision Pathology 14. Computational Pathology 15. Digital Neuropathology 16. Application of Artificial Intelligence (AI) in Gastrointestinal Endoscopy 17. Digital Transformation Processes in Acute Inpatient Care in Germany 18. Digital Medicine in Neurology 19. Neurorehabilitation Medicine 20. Digital Psychiatry 21. Digital Neurosurgery 22. Digital Surgery: The Convergence of Robotics, Artificial Intelligence and Big Data 23. Digital Urology 24. Digitalization in Anesthesiology and Intensive Care 25. Digital Palliative Care 26. Digital Medicine in Pulmonary Medicine 27. Digital Rheumatology 28. Digital Dermatology 29. Digital Neonatology 30. Digital Medicine and Artificial Intelligence in the Area of Breast and Gynaecologic Cancer 31. Digital Otorhinolaryngology (Ear-Nose-Throat) 32. Digital Orthopedics and Traumatology
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Produktdetaljer

ISBN
9789814968737
Publisert
2023-06-09
Utgiver
Vendor
Jenny Stanford Publishing
Vekt
1280 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
682

Forfatter

Biographical note

Ralf Huss is an adjunct professor of pathology at the Institute of Pathology and Molecular Diagnostics, University Hospital Augsburg (Germany), where he also founding director of the Institute for Digital Medicine, before he assumed the role of the managing director of BioM Biotech Cluster Development GmbH in Munich (Germany). Dr. Huss is board certified in anatomical, experimental, and molecular pathology with more than 30 years of training and experience in histopathology, immunology, translational cancer research, and oncology in Zurich (Switzerland), Seattle (USA), and Munich (Germany). He has also held different senior positions in the pharmaceutical industry at Roche and AstraZeneca. He also serves as an honorary professor at the University College Dublin (Ireland) and as a lecturer of nanotechnology and biomaterials at the Faculty of Chemistry, Technical University of Munich (Germany). His research focuses on the use of machine and artificial intelligence in routine tissue diagnostics and biomarker discovery, and he has (co-)authored more than 150 peer-reviewed articles, reviews, book chapters, and books in related areas.