AI, Machine Learning, and Ethics in Health Care
Abstract
.
Integrity signals
Registry
Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI systems are only as good as the data provided to them.
“AI systems are only as good as the data provided to them”
From Ethics and governance of trustworthy medical artificial intelligence (2023) · cites this paper as [18]
Wang et al. identified that XAI could support different explanation types by articulating how people understand events or observations through explanations and can be leveraged to mitigate decision biases and cognitive biases.
“Wang et al. [118] identified that XAI could support different explanation types by articulating how people understand events or observations through explanations and can be leveraged to mitigate decision biases and cognitive biases [98,103,112].”
From Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review (2021) · cites this paper as [112]
Cited by
Sorted by citations
Antoniadi, A. M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B. A., & Mooney, C. (2021) · Applied Sciences · doi:10.3390/app11115088 · Cited by 629 · see citing works
Ethics and governance of trustworthy medical artificial intelligence
Zhang, J., & Zhang, Z.-M. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02103-9 · Cited by 507 · see citing works
Singhal, A., Neveditsin, N., Tanveer, H., & Mago, V. (2024) · JMIR Medical Informatics · doi:10.2196/50048 · Cited by 172 · see citing works
- Authors
- Johnson, S. L. J.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Johnson, Sandra L. J.
- Venue
- Journal of Legal Medicine
- Publisher
- Informa UK Limited
- Published
- 2019-10-02
- Volume
- 39
- Issue
- 4
- Pages
- 427-441
- ISSN
- 0194-7648 (ISSN-L)
- 1521-057X
- OpenAlex
- W2999828647
- Cited by
- 53
- References
- 0
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 17 · 2023: 7 · 2022: 7 · 2021: 3 · 2020: 1
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Legal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Keywords
- artificial intelligence, machine learning, ethics, health care, medical ethics
- MeSH terms
- Machine Learning, Health Equity, Data Science, Artificial Intelligence, Bioethics, Confidentiality, Congresses as Topic, Informed Consent, Legislation as Topic, Social Justice, Social Responsibility, Neural Networks, Computer, Personal Autonomy, Beneficence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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