Artificial Intelligence in Healthcare (eBook, ePUB)

Redaktion: Bohr, Adam; Memarzadeh, Kaveh

• Format: ePub

Produktbeschreibung

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction toartificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 378
• Erscheinungstermin: 21. Juni 2020
• Englisch
• ISBN-13: 9780128184394
• Artikelnr.: 61688778

Autorenporträt

Adam Bohr holds a PhD in Biomedical Engineering (2013) from University College London and has over a decade of experience in pharmaceutical and healthcare sciences across both academia and industry. He currently works at Novo Nordisk, where he leads AI and digital transformation initiatives in drug discovery and development. Dr. Bohr has a strong background in applying artificial intelligence to healthcare and in addition to his industry role, he is the founder and technical lead of Sonohaler, a company developing AI-driven solutions to support the management of respiratory conditions. His expertise spans the full spectrum of AI applications in healthcare, from early-stage research to real-world deployment. Dr. Bohr is also the co-editor of the book, Artificial Intelligence in Healthcare, which received wide recognition and readership and has a solid track record of peer-reviewed publications.

Kaveh Memarzadeh, PhD is currently a Senior Manager at ChemoMetec, a biotechnology company that innovates in the field of automated cell cytometry. He holds research affiliations with University College London and Queen Mary University. He previously oversaw research management and communications at Orthopaedic Research UK (ORUK), a UK based medical charity that funds projects into the betterment and improvement of human movement and augmentation. He has published numerous peer-reviewed academic papers and has a PhD in nanotechnology, biomaterials and microbiology. He is also a visiting lecturer at University College London, teaching on a range of topics from the future of prosthetics/bionics to utilization of nanotechnology for antimicrobial bone implants. In his spare time, he reads, paints, builds his own gaming computers and utilizes the power of social media to share his passion for nature with hundreds of thousands of people.

Inhaltsangabe

List of contributors xi

About the editors xiii

Biographies xv

Preface xxi

Introduction xxiii

1. Current healthcare, big data, and machine learning 1

Adam Bohr and Kaveh Memarzadeh

1.1 Current healthcare practice 1

1.2 Value-based treatments and healthcare services 5

1.3 Increasing data volumes in healthcare 10

1.4 Analytics of healthcare data (machine learning and deep learning) 16

1.5 Conclusions/summary 21

References 22

2. The rise of artificial intelligence in healthcare applications 25

Adam Bohr and Kaveh Memarzadeh

2.1 The new age of healthcare 25

2.2 Precision medicine 28

2.3 Artificial intelligence and medical visualization 33

2.4 Intelligent personal health records 38

2.5 Robotics and artificial intelligence-powered devices 43

2.6 Ambient assisted living 46

2.7 The artificial intelligence can see you now 50

References 57

3. Drug discovery and molecular modeling using artificial intelligence 61

Henrik Bohr

3.1 Introduction. The scope of artificial intelligence in drug discovery 61

3.2 Various types of machine learning in artificial intelligence 64

3.3 Molecular modeling and databases in artificial intelligence for drug

molecules 70

3.4 Computational mechanics ML methods in molecular modeling 72

3.5 Drug characterization using isopotential surfaces 74

3.6 Drug design for neuroreceptors using artificial neural network techniques 75

3.7 Specific use of deep learning in drug design 78

3.8 Possible future artificial intelligence development in drug design and

development 80

References 81

4. Applications of artificial intelligence in drug delivery and pharmaceutical development 85

Stefano Colombo

4.1 The evolving pharmaceutical field 85

4.2 Drug delivery and nanotechnology 89

4.3 Quality-by-design R&D 92

4.4 Artificial intelligence in drug delivery modeling 95

4.5 Artificial intelligence application in pharmaceutical product R&D 98

4.6 Landscape of AI implementation in the drug delivery industry 109

4.7 Conclusion: the way forward 110

References 111

5. Cancer diagnostics and treatment decisions using artificial intelligence 117

Reza Mirnezami

5.1 Background 117

5.2 Artificial intelligence, machine learning, and deep learning in cancer 119

5.3 Artificial intelligence to determine cancer susceptibility 122

5.4 Artificial intelligence for enhanced cancer diagnosis and staging 125

5.5 Artificial intelligence to predict cancer treatment response 127

5.6 Artificial intelligence to predict cancer recurrence and survival 130

5.7 Artificial intelligence for personalized cancer pharmacotherapy 133

5.8 How will artificial intelligence affect ethical practices and patients? 136

5.9 Concluding remarks 137

References 139

6. Artificial intelligence for medical imaging 143

Khanhvi Tran, Johan Peter Bøtker, Arash Aframian and Kaveh Memarzadeh

6.1 Introduction 143

6.2 Outputs of artificial intelligence in radiology/medical imaging 144

6.3 Using artificial intelligence in radiology and overcoming its hurdles 146

6.4 X-rays and artificial intelligence in medical imaging-case 1 (Zebra medical

vision) 151

6.5 Ultrasound and artificial intelligence in medical imaging-case 2

(Butterfly iQ) 156

6.6 Application of artificial intelligence in medical imaging-case 3 (Arterys) 158

6.7 Perspectives 160

References 161

7. Medical devices and artificial intelligence 163

Arash Aframian, Farhad Iranpour and Justin Cobb

7.1 Introduction 163

7.2 The development of artificial intelligence in medical devices 163

7.3 Limitations of artificial intelligence

Rezensionen

"This book is overall a very complete and organized book that gives newly interested persons a look at AI and its applications. The first few chapters give readers a chance to get used to the vocabulary and give small but effective diagrams explaining often confused concepts such as machine learning versus deep learning. The first few chapters may be extremely dry if the readers are fairly familiar with AI. Therefore, I would recommend this book for readers who feel unsure of their foundation in AI. I would say of the books I have read on digital health in general, this book is more focused. If you compare to Data Pulse: A Brief Tour of Artificial Intelligence in Healthcare, Marcetich (New Degree Press, 2020) or Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, Topal (Basic Books, 2019), both put a focus on challenges of AI, whereas this book has a large focus on the opportunities and covers them in great detail." --Doody Reviews