Precision Health and Artificial Intelligence: With Privacy, Ethics, Bias, Health Equity, Best Practices, and Case Studies
- Length: 191 pages
- Edition: 1
- Language: English
- Publisher: Apress
- Publication Date: 2023-03-03
- ISBN-10: 1484291611
- ISBN-13: 9781484291610
- Sales Rank: #0 (See Top 100 Books)
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
Table of Contents About the Author About the Technical Reviewer Acknowledgments Introduction Chapter 1: Introduction From Personalized Medicine to Precision Health Why Precision Health? Why Now? Shifting Paradigms from Volume to Value Social Determinants of Health Why Diversity Is Essential Within Precision Health Summary Chapter 2: What Is Precision Health? The Five Ps of Precision Health Prediction and Prevention Personalization of Treatment Participation Population Considerations of Precision Health Cost Genes Are Just the Beginning Health Equality Unfulfilled Power of Data Engagement High Touch Means High Tech Phenomics Digital Transformation Applying Precision Health: The P5H Precision Healthcare Continuum Health Stages Stage A Stage B Stage C Stage D Optimization Across Stages Intervention Levels Level 1 Level 2 Level 3 Level 4 Summary Chapter 3: Data and the Digital Phenotype Data Forms and Types Forms Types Sources of Data Sensors Digital Phenotyping Digital Twin Data Challenges Measurement and Completeness Lack of Data on Social Determinants of Health Privacy and Security Cost Disconnected from Data Limited Adoption of Common Data Models Expanding Beyond Qualitative Data A Paradigm for Acting on Data Turning Data into Information, Knowledge, and Wisdom Summary Chapter 4: Artificial Intelligence and Machine Learning in Precision Health The Three Types of AI Artificial Narrow Intelligence Artificial General Intelligence Artificial Superintelligence A Brief Introduction to Machine Learning Framework for Machine Learning Software and Toolkits Explainable AI Applications of AI Assisted Precision Health in Practice Clinical Decision Support Behavioral Change Interventions and Lifestyle Medicine New Treatments, Definitions of Disease, and Points of Intervention Digital Twins Health Promoting Chatbots Voice Recognition Summary Chapter 5: Risks and Ethical Challenges of Precision Health Responsible Development and Ethical AI Principles Epistemic Principles Interpretability Reliability and Safety General Ethical AI Principles Bias, Inclusivity, and Fairness Transparency and Accountability Lawfulness Data Privacy and Security Human Agency Beneficence Redesigning Care and the Patient-Clinician Relationship Health Inequalities Theology Preparing the Profession Summary Chapter 6: Future of Precision Healthcare Precision Care from Birth to Death Nanotechnology DNA Manipulation and Gene Therapy Smart Sensors Bioprinting Brain Computer Interfacing Smart Habitats Digital Health Education Literacy Changing Roles Quality Ability Accessibility and Equity New Forms of Training Collaboration Between Academia and Industry Summary Chapter 7: Precision Healthcare in Practice Delivery of Specialist Multidisciplinary Weight Management to Hospital-Based Patients Through a Digital Tool Objective Methods How Does Personalization Appear? Results Discussion Conclusion Building on Our Evidence Understanding People’s Attitudes Toward Data for the Optimization of a Specialist Podiatry Service for People with Long-Term Health Conditions Objective Methods Results Discussion Conclusion Impact of the Findings Evaluation of a Digital Intervention for the Self-Management of Type 2 Diabetes and Prediabetes Objectives Methods Results Discussion Conclusion Impact of the Findings Voice-Based Symptom Monitoring and AI-Based Rehabilitation for Patients with Long COVID Background Objective Implementation Plan Risks Evaluation Potential Impact Developing a Digital Tool to Support Daily Behavioral Change for Children and Young People to Support Healthier Lives Objective Methods Milestones Evaluation Impact of the Project Summary Index
Donate to keep this site alive
How to download source code?
1. Go to: https://github.com/Apress
2. In the Find a repository… box, search the book title: Precision Health and Artificial Intelligence: With Privacy, Ethics, Bias, Health Equity, Best Practices, and Case Studies
, sometime you may not get the results, please search the main title.
3. Click the book title in the search results.
3. Click Code to download.
1. Disable the AdBlock plugin. Otherwise, you may not get any links.
2. Solve the CAPTCHA.
3. Click download link.
4. Lead to download server to download.