Regulation of predictive analytics in medicine
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Algorithms must meet regulatory standards of clinical benefit
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As AI-based devices are not in line with traditional medical practices, the ambiguity about the safety and efficacy of AI models in healthcare are still strong reasons that facilitate users' risks.
“As AI-based devices are not in line with traditional medical practices, the ambiguity about the safety and efficacy of AI models in healthcare are still strong reasons that facilitate users’ risks [51].”
From Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives (2020) · cites this paper as [51]
Lacking jurisprudence from the European General Data Protection Regulation and the new Medical Device Regulation leads to several regulatory and legal uncertainties for AI applications in radiology.
“lacking jurisprudence from the European General Data Protection Regulation and the new Medical Device Regulation (MDR), which will come into effect in May 2020, leads to several regulatory and legal uncertainties for AI applications in radiology [32, 33].”
From Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors (2020) · cites this paper as [32]
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- Authors
- Parikh, R. B., Obermeyer, Z., & Navathe, A. S.
- Affiliations
- Leonard Davis Institute of Health Economics (US)
- University of California, Berkeley (US)
- Philadelphia VA Medical Center (US)
- Venue
- Science
- Published
- 2019-02-22
- Volume
- 363
- Issue
- 6429
- Pages
- 810-812
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6557272
- OpenAlex
- W2915444077
- Cited by
- 223
- References
- 8
- Citations by year
- 2026: 28 · 2025: 45 · 2024: 25 · 2023: 20 · 2022: 19 · 2021: 33 · 2020: 30 · 2019: 21
- FWCI
- 8.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Robert Wood Johnson Foundation
- Pennsylvania Department of Health
- National Institutes of Health (DP5OD012161)
- U.S. Food and Drug Administration
- National Cancer Institute (T32CA009615)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Health Professions › Health Information Management › Healthcare Regulation
- Keywords
- predictive analytics, algorithm regulation, clinical benefit, artificial intelligence in healthcare, regulatory standards, clinical decision support
- MeSH terms
- Algorithms, Artificial Intelligence, Decision Support Techniques, Humans, United States, United States Food and Drug Administration, Evidence-Based Medicine, Benchmarking
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