Randomized clinical trials of artificial intelligence
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AI will change how clinical research is performed, improving evidence-based medicine and conducting randomized clinical trials.
“AI will change how clinical research is performed, improving evidence-based medicine and conducting randomized clinical trials (RCTs) [62].”
From Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22. (2025) · cites this paper as [62]
Few randomized controlled trials of AI-based digital health interventions have been published which are needed to generate robust evidence of its effectiveness in improving outcomes.
“Furthermore, few randomized controlled trials of AI-based digital health interventions have been published which are needed to generate robust evidence of its effectiveness in improving outcomes (Angus, 2020).”
From The application and use of artificial intelligence in cancer nursing: A systematic review (2024) · cites this paper as Angus, 2020
Cites
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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 · see citing works
Abràmoff, M. D., Lavin, P. T., Birch, M., Shah, N., & Folk, J. C. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0040-6 · Cited by 1,638 · see citing works
Komorowski, M., Celi, L. A., Badawi, O., Gordon, A. C., & Faisal, A. A. (2018) · Nature Medicine · doi:10.1038/s41591-018-0213-5 · Cited by 1,290 · see citing works
Addressing bias in artificial intelligence in health care
Parikh, R. B., Teeple, S., & Navathe, A. S. (2019) · JAMA · doi:10.1001/jama.2019.18058 · Cited by 764 · see citing works
Deep Learning—A Technology With the Potential to Transform Health Care
Hinton, G. (2018) · JAMA · doi:10.1001/jama.2018.11100 · Cited by 667 · see citing works
Hatib, F., Jian, Z., Buddi, S., Lee, C., Settels, J., Sibert, K., Rinehart, J., & Cannesson, M. (2018) · Anesthesiology · doi:10.1097/aln.0000000000002300 · Cited by 614 · see citing works
Wijnberge, M., Geerts, B. F., Hol, L., Lemmers, N., Mulder, M. P., Berge, P., Schenk, J., Terwindt, L. E., Hollmann, M. W., Vlaar, A. P., et al. (2020) · JAMA · doi:10.1001/jama.2020.0592 · Cited by 586 · see citing works
Questions for artificial intelligence in health care
Maddox, T. M., Rumsfeld, J. S., & Payne, P. R. O. (2019) · JAMA · doi:10.1001/jama.2018.18932 · Cited by 385 · see citing works
Artificial Intelligence in Health Care: Will the Value Match the Hype?
Emanuel, E. J., & Wachter, R. M. (2019) · JAMA · doi:10.1001/jama.2019.4914 · Cited by 237 · see citing works
Unsupervised Analysis of Transcriptomic Profiles Reveals Six Glioma Subtypes
Li, A., Walling, J., Ahn, S. J., Kotliarov, Y., Su, Q., Quezado, M., Oberholtzer, J. C., Park, J., Zenklusen, J. C., & Fine, H. A. (2009) · Cancer Research · doi:10.1158/0008-5472.can-08-2100 · Cited by 220 · see citing works
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Evaluating the collection, comparability and findings of six global surgery indicators
Holmer, H., Bekele, A., Hagander, L. E., Harrison, E. M., Kamali, P., Ng-Kamstra, J., Khan, M. A., Knowlton, L. M., Leather, A. J. M., Marks, I. H., et al. (2018) · British journal of surgery · doi:10.1002/bjs.11061 · Cited by 117 · see citing works
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Artificial intelligence in nursing and midwifery: A systematic review
O'Connor, S., Yan, Y., Thilo, F. J. S., Felzmann, H., Dowding, D., & Lee, J. J. (2023) · Journal of Clinical Nursing · doi:10.1111/jocn.16478 · Cited by 351 · see citing works
Artificial intelligence in oncology: path to implementation
Chua, I. S., Gaziel‐Yablowitz, M., Korach, Z. T., Kehl, K. L., Levitan, N. A., Arriaga, Y. E., Jackson, G. P., Bates, D. W., & Hassett, M. (2021) · Cancer Medicine · doi:10.1002/cam4.3935 · Cited by 179 · see citing works
Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.
Cecconi, M., Greco, M., Shickel, B., Angus, D. C., Bailey, H., Bignami, E., Calandra, T., Celi, L. A., Einav, S., Elbers, P., et al. (2025) · Critical Care · doi:10.1186/s13054-025-05532-2 · Cited by 80 · see citing works
“AI will change how clinical research is performed, improving evidence-based medicine and conducting randomized clinical trials (RCTs) [62].”
Self-citationKamran, F., Tang, S., Otles, E., McEvoy, D. S., Saleh, S. N., Gong, J., Li, B. Y., Dutta, S., Liu, X., Medford, R. J., et al. (2022) · BMJ · doi:10.1136/bmj-2021-068576 · Cited by 60 · see citing works
The application and use of artificial intelligence in cancer nursing: A systematic review
O'Connor, S., Vercell, A., Wong, D., Yorke, J., Fallatah, F. A., Cave, L., & Anny Chen, L.-Y. (2024) · European Journal of Oncology Nursing · doi:10.1016/j.ejon.2024.102510 · Cited by 51 · see citing works
Reimagining cancer treatments in the era of generative AI
Derbal, Y. (2025) · DIGITAL HEALTH · doi:10.1177/20552076251394631 · Cited by 4 · see citing works
- Authors
- Angus, D. C.
- Affiliations
- University of Pittsburgh (US)
- Corresponding author
- Angus, Derek C.
- ORCID
- Angus, Derek C.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2020-03-17
- Volume
- 323
- Issue
- 11
- Pages
- 1043
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W3005745869
- Cited by
- 112
- References
- 13
- Citations by year
- 2026: 14 · 2025: 21 · 2024: 17 · 2023: 11 · 2022: 15 · 2021: 23 · 2020: 11
- 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
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- artificial intelligence, randomized controlled trials, trial design
- MeSH terms
- Machine Learning, Artificial Intelligence, Humans, Hypotension, Randomized Controlled Trials as Topic, Elective Surgical Procedures
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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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