The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Questions for Artificial Intelligence in Health Care
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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
“This may reduce the accuracy and generalisability of the predictive models, a drawback of AI that has been widely reported in the healthcare literature (Maddox et al., 2019).”
From The application and use of artificial intelligence in cancer nursing: A systematic review (2024) · cites this paper as Maddox et al., 2019
Citations
Cites
Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., Cuadros, J., et al. (2016) · JAMA · doi:10.1001/jama.2016.17216 · Cited by 7,697
Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data
Gianfrancesco, M. A., Tamang, S., Yazdany, J., & Schmajuk, G. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.3763 · Cited by 1,395
Zhang, J., Gajjala, S., Agrawal, P., Tison, G. H., Hallock, L. A., Beussink-Nelson, L., Lassen, M. H., Fan, E., Aras, M. A., Jordan, C., et al. (2018) · Circulation · doi:10.1161/circulationaha.118.034338 · Cited by 1,006
What This Computer Needs Is a Physician: Humanism and Artificial Intelligence
Verghese, A., Shah, N. H., & Harrington, R. A. (2018) · JAMA · doi:10.1001/jama.2017.19198 · Cited by 468
Clinical Implications and Challenges of Artificial Intelligence and Deep Learning
Stead, W. W. (2018) · JAMA · doi:10.1001/jama.2018.11029 · Cited by 250
Cited by
Sorted by citations
Artificial Intelligence in Dentistry: Chances and Challenges
Schwendicke, F., Samek, W., & Krois, J. (2020) · Journal of Dental Research · doi:10.1177/0022034520915714 · Cited by 1,446
Artificial intelligence literacy in higher and adult education: A scoping literature review
Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100101 · Cited by 658
Cai, C. J., Winter, S., Steiner, D., Wilcox, L., & Terry, M. (2019) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3359206 · Cited by 594
Peiffer-Smadja, N., Rawson, T. M., Ahmad, R., Buchard, A., Georgiou, P., Lescure, F.-X., Birgand, G., & Holmes, A. H. (2020) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2019.09.009 · Cited by 561
Towards a standard for identifying and managing bias in artificial intelligence
Schwartz, R., Vassilev, A., Greene, K., Perine, L., Burt, A., & Hall, P. (2022) · doi:10.6028/nist.sp.1270 · Cited by 548
Metadata
- Authors
- Maddox, T. M., Rumsfeld, J. S., & Payne, P. R. O.
- Affiliations
- BJC HealthCare (US)
- American College of Cardiology (US)
- Washington University in St. Louis (US)
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2019-01-01
- Volume
- 321
- Issue
- 1
- Pages
- 31
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2904251400
- Cited by
- 385
- References
- 5
- Citations by year
- 2026: 28 · 2025: 52 · 2024: 38 · 2023: 91 · 2022: 45 · 2021: 56 · 2020: 44 · 2019: 31
- FWCI
- 8.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JAMA (publishedVersion)
- PubMed (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 › Machine Learning in Healthcare
- Keywords
- artificial intelligence, health care, clinical decision support
- MeSH terms
- Artificial Intelligence, Decision Making, Computer-Assisted, Humans, Patient Care Management, Datasets as Topic
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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