Artificial Intelligence in Medicine
From Ethical, Social, and Legal Perspectives
- 1st Edition - March 13, 2024
- Imprint: Academic Press
- Editors: Joseph JY Sung, Cameron Stewart
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 5 0 6 8 - 8
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 5 0 6 9 - 5
Artificial Intelligence in Medicine: From Ethical, Social, and Legal Perspectives provides answers on how to improve acceptance and diminish the anxiety of the use of AI-ass… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteArtificial Intelligence in Medicine: From Ethical, Social, and Legal Perspectives provides answers on how to improve acceptance and diminish the anxiety of the use of AI-assisted medicine. Through a series of social, ethical, and legal discussions from clinicians, social scientists, ethicists, and legal experts, this important reference has coverage that includes good data custodianship and stewardship, data access, data bias, data & healthcare equity, privacy and confidentiality, algorithmic understanding, and regulatory guidance, accountability, and legal responsibility.
This reference will explain to healthcare providers how AI will enhance healthcare, will introduce to scientists and researchers the ethical and social aspect of AI that needs to be addressed, and will urge policymakers and health authorities to consider the legal framework needed to implement AI technology in healthcare.
This reference will explain to healthcare providers how AI will enhance healthcare, will introduce to scientists and researchers the ethical and social aspect of AI that needs to be addressed, and will urge policymakers and health authorities to consider the legal framework needed to implement AI technology in healthcare.
- Discusses the issues that must be addressed to improve acceptance and diminish the anxiety and lack of trust surrounding the care of human health by machines
- Examines the delicate issues surrounding the use of AI in making life-and-death decisions
- Sets the framework of social, ethical, and legal aspects of healthcare for the future
Healthcare providers, specifically medical doctors who are taking care of patients and need to work with AI in providing care and need to know the capabilities of AI, the role they play in using AI-assisted medicines, and the ethical-social aspects of such applications, Engineers who are working on developing AI tools for the application in medicine. They need to understand the hurdle and challenges one has to overcome to put technology on the ground for clinical applications
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Chapter 1 Artificial intelligence and the future of medicine
- Abstract
- Introduction
- What are the capabilities of AI in 2023?
- Image-based analysis and diagnosis
- Clinical decision support and application of precision medicine
- Prediction of health conditions and treatment outcome
- Improving accessibility of healthcare and empowering patients with lifestyle modification and compliance to treatment
- Drug and diagnostic test discovery
- ChatGPT
- Successful implementation of AI in medicine
- Obstacles to overcome for implementation of AI in medicine
- Engaging the clinicians and healthcare providers
- Successful implementation of AI in medicine
- References
- Chapter 2 Data access, data bias, data equity
- Abstract
- Introduction
- Definition of terms
- Data access
- Data bias
- Data equity
- Algorithmic stewardship as a framework for mitigation strategy against bias and inequity
- References
- Chapter 3 Respect for persons
- Abstract
- Introduction
- A values-based deliberative balancing approach to ethical decision-making
- Case study: Applying the Framework to AI-assisted PDSS
- Conclusion
- References
- Chapter 4 Privacy and confidentiality
- Abstract
- Introduction
- Personal health information (PHI)
- Privacy
- Confidentiality
- Privacy and confidentiality in medical and health services
- Privacy crossing paths with confidentiality
- Exemptions from privacy breaches
- Data protection principles (DPP)
- Accountability
- Consent
- Enhanced privacy rights
- Data ethics
- AI and digital data ethics in med-health sciences and services
- From a privacy structure to a privacy culture
- References
- Chapter 5 Black box medicine
- Abstract
- Introduction
- The three stages of AI development with five principles
- Data collection
- Transparency
- Privacy of data
- Models and algorithm development
- Black box medicine: What is acceptable?
- References
- Chapter 6 Clinical evidence
- Abstract
- Introduction
- What is AI in clinical medicine?
- Case examples
- What is needed for AI?
- Barriers of AI
- Future of AI
- Conclusion
- References
- Chapter 7 Medical AI and tort liability
- Abstract
- Acknowledgments
- Introduction
- Liability for medical AI
- Malpractice liability and the standard of care
- Regulation and preemption as alternative to the common law of torts
- Conclusion
- References
- Chapter 8 Regulation of AI in healthcare
- Abstract
- Introduction
- What do we mean by “regulation”?
- What should be regulated?
- Premarket regulation
- Postmarket regulation
- Transparency and consent
- Devices or practitioners?
- References
- Chapter 9 Health inequalities in AI machine learning
- Abstract
- Acknowledgment
- Introduction
- Biases in AI machine learning
- Impact of AI on social determinants of health
- Conclusion
- References
- Chapter 10 Human-machine interaction: AI-assisted medicine, instead of AI-driven medicine
- Abstract
- Introduction
- Implementation is the challenge
- Human-machine interaction
- AI-CDSSs as clinical team members
- Conclusion
- References
- Index
- Edition: 1
- Published: March 13, 2024
- Imprint: Academic Press
- No. of pages: 300
- Language: English
- Paperback ISBN: 9780323950688
- eBook ISBN: 9780323950695
JS
Joseph JY Sung
Joseph Sung is a MD, PhD, Dean of Medicine and Senior Vice President of Nanyang Technological University Singapore. He was President and Vice Chancellor of the Chinese University of Hong Kong 2010-2017 and President of the World University Network 2016-2018. With 30 years of experience in academic medicine, he has published over 1,000 scientific papers and review articles, and nominated highly cited research in 2018, 2019 and 2020 by Clarivate Web of Science. In recent years, his interest has turned into the use of artificial intelligence in Medicine.
Affiliations and expertise
Distinguished University Professor & Dean, Lee Kong Chian School of Medicine; Senior Vice President (Health and Life Sciences) Nanyang Technological UniversityCS
Cameron Stewart
Cameron Stewart BEc LLB, PhD, is a member of Sydney Health Law and an associate of the Centre for Values, Ethics and the Law in Medicine, Professor of Health, Law and Ethics at the University of Sydney Law School. He was acting Dean of Law in Sydney Law School, acting president of the Australian and New Zealand Institute of Health Law and Ethics in 2008-2010 and was the Vice-President of the Australasian Association of Bioethics and Health Law from 2010-2013.
Affiliations and expertise
Associate Professor of Law, Macquarie University Honorary Associate Professor of Law, Centre for Values in Ethics, Medicine and the Law, University of Sydney, Legal Practitioner, NSW Supreme Court Barrister and Solicitor, High Court of AustraliaRead Artificial Intelligence in Medicine on ScienceDirect