Precision Health and Artificial Intelligence: With Privacy, Ethics, Bias, Health Equity, Best Practices, and Case Studies

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