The DOI matches its Crossref record.
Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril
Overview
Integrity signals
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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?
In the citing paper
“The US National Academy of Medicine issued a reference document for the responsible development and maintenance of AI in the clinical setting that provides a guiding framework for all stakeholders, including AI developers and the medical community99.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [99]
Citations
Cited by
Sorted by citations
Smart wearable devices in cardiovascular care: Where we are and how to move forward
Bayoumy, K., Gaber, M., Elshafeey, A., Mhaimeed, O., Dineen, E. H., Marvel, F. A., Martin, S. S., Muse, E. D., Turakhia, M. P., Tarakji, K. G., et al. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00522-7 · Cited by 829
Artificial intelligence for good health: a scoping review of the ethics literature.
Murphy, K., Di Ruggiero, E., Upshur, R., Willison, D. J., Malhotra, N., Cai, J. C., Malhotra, N., Lui, V., & Gibson, J. (2021) · BMC Medical Ethics · doi:10.1186/s12910-021-00577-8 · Cited by 435
Identifying Ethical Considerations for Machine Learning Healthcare Applications
Char, D. S., Abràmoff, M. D., & Feudtner, C. (2020) · The American Journal of Bioethics · doi:10.1080/15265161.2020.1819469 · Cited by 415
Artificial intelligence in medical education: a cross-sectional needs assessment
Civaner, M. M., Uncu, Y., Bulut, F., Chalil, E. G., & Tatli, A. (2022) · BMC Medical Education · doi:10.1186/s12909-022-03852-3 · Cited by 363
Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals
Russell, R. G., Lovett Novak, L., Patel, M., Garvey, K. V., Craig, K. J. T., Jackson, G. P., Moore, D., & Miller, B. M. (2023) · Academic Medicine · doi:10.1097/acm.0000000000004963 · Cited by 320
Metadata
- Authors
- Series, T. L. H. S., & National Academy of Medicine
- Corresponding author
- The Learning Health System Series
- Venue
- National Academies Press eBooks
- Publisher
- National Academies Press
- Published
- 2019-08-02
- OpenAlex
- W4385490920
- Cited by
- 227
- References
- 0
- Citations by year
- 2026: 32 · 2025: 54 · 2024: 38 · 2023: 32 · 2022: 39 · 2021: 24 · 2020: 8
- FWCI
- 3.80
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- National Academies Press eBooks (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence, health care, health care delivery, clinical decision support, health information technology
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.
Statistics and arithmetic are recomputed, not judged.
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