Artificial intelligence, machine learning, and bioethics in clinical medicine
Book Title
Machine Learning and Artificial Intelligence in Radiation Oncology A Guide for Clinicians
Files
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Editors
Kang J, Rattay T, Rosenstein BS
Description
Artificial intelligence and machine learning (AI/ML), as outlined in this book, promise to assist with certain empirical uncertainties, but may also produce new and vexing ethical questions in the context of clinical care. Similarly, in the context of research, ethical challenges of informed consent, transparency, and equity abound. In this chapter, we present several important concepts to help frame the ethical challenges of AI/ML in medicine and elaborate several key ethical questions that the field will face in the coming decades. We then offer a set of recommendations for radiation oncologists, and clinicians more broadly, to begin to address complexities inherent in existing and emerging AI/ML technologies.
First Page
29
Last Page
39
ISBN
9780128220016
Publication Date
12-2023
Publisher
Elsevier Science
City
San Diego
Keywords
artificial intelligence, machine learning, radiation oncology
Disciplines
Bioethics and Medical Ethics
Recommended Citation
Wasserman JA, Wald HS. Artificial intelligence, machine learning, and bioethics in clinical medicine. In: Kang J, Rattay T, Rosenstein BS, eds. Machine learning and artificial intelligence in radiation oncology: a Guide for clinicians. San Diego CA: Elsevier Science, 2023, p.29-39.