Precision Health and Artificial Intelligence

With Privacy, Ethics, Bias, Health Equity, Best Practices, and Case Studies
1. Auflage 2023
ISBN: 978-1-4842-9161-0
Verlag: Apress

Buch, Englisch, 172 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 300 g

This book provides a comprehensive explanation of precision (i.e., personalized) healthcare and explores how it can be advanced through artificial intelligence (AI) and other data-driven technologies.

From improving the diagnosis, treatment, and monitoring of many medical conditions to the effective implementation of precise patient care, this book will help you understand datasets produced from digital health technologies and IoT and teach you how to employ analytical methods such as convolutional neural networks and deep learning to analyze that data. You’ll also see how this data-driven approach can enhance and democratize value-based healthcare delivery. Additionally, you’ll learn how the convergence of AI and precision health is revolutionizing healthcare, including some of the most difficult challenges facing precision medicine, such as ethics, bias, privacy, and health equity. 

Precision Health and Artificial Intelligence provides the groundwork for clinicians, engineers, bioinformaticians, and healthcare enthusiasts to apply AI to healthcare.

What You Will Learn

• Understand the components required to facilitate precision health and personalized care
• Apply and implement precision health systems
• Overcome the challenges of delivering precision healthcare at scale
• Reconcile ethical and moral implications of delivering precision healthcare
• Gain insight into the hurdles providers face while implementing precision healthcare 

Who This Book Is For
Healthcare professionals, clinicians, engineers, bioinformaticians, chief information officers (CIOs), and students

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Panesar, Arjun

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Betriebliches Gesundheitsmanagement
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

Chapter 1:  Introduction to Precision Health and Artificial IntelligenceChapter Goal: An introduction to precision health, the concepts of AI-wearables, health data and health tech and how they transform the health industry No of pages: 15
Chapter 2:  Foundations of Precision HealthChapter Goal: A deep dive into precision health including key principles and processes.No of pages: 25 Chapter 3: DataChapter Goal: Data has been the beginning of many great products, services or ventures in health tech — explore types of data, and how they can be used.No of pages: 25Sub - Topics:       1.    Little and big data2.    Types of data3.    Wearables and IoT, genomics4.    Using data to enable precision health Chapter 4: Artificial Intelligence in Precision HealthChapter Goal: Concepts and ideas in artificial intelligence (AI) and machine learning -- including statistical approaches, visualization, human-computer interactions and evaluating health AI.Pages: 251.    Statistical approaches2.    Visualization3.    Human computer interaction4.    Evaluations of AI
Chapter 5: Ethics and RegulatoryChapter Goal: An in-depth study of legal, ethical, and regulatory concepts in precision health.No of pages: 35Sub - Topics:1.Ethics2.Legal3.Regulatory concerns  Chapter 6: Case Studies: The Application of Artificial Intelligence in Precision Healthcare and MedicineChapter Goal:      Applications of AI techniques and software tools. This will primarily involve exploring recent examples of AI and Machine Learning tools being specifically used to aid in clinical practice.Pages: 251. Best case examples of AI to aid clinical practice

Über Autor(innen)

Arjun Panesar is the founder of DDM Health, a multi-award-winning provider of digital therapeutics to over 1.8 million people. He holds a first-class honors degree (MEng) in Computing and Artificial Intelligence (AI) from Imperial College, London, and has more than two decades of experience in big data and AI. Arjun leads the development of evidence-based digital innovations that harness the power of machine learning to provide precision health and medicine to patients, health services, and governments worldwide. His work has received recognition from the BBC, Forbes, New Scientist, and The Times, and has been awarded an array of innovation, business, and technology awards. Most recently, DDM Health’s apps were recognized as the highest-rated digital health apps in Europe.
Arjun is an advisor to the Information School, University of Sheffield, an Honorary Clinical Lecturer in precision healthcare and AI at Warwick Medical School, University of Warwick, an Alumni Fellow to the NHS Innovation Accelerator, and recognized by Imperial College as an Emerging Alumni Leader in 2020 for his contribution and impact to health.