PreprintCited by 48Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AIEthics in Clinical Research

The Ethics of AI in Biomedical Research, Patient Care and Public Health

Open access
Blasimme, Alessandro, Vayena, Effy·2019·SSRN Electronic Journal

Integrity signals

Registry

Crossref · 10.2139/ssrn.3368756

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

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Claims the paper makes

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Claims other papers make about this one

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  • The use of AI holds substantial promise in enhancing the efficiency and effectiveness of distributing limited medical resources.

    “In the critical area of resource allocation within health care, the use of AI holds substantial promise in enhancing the efficiency and effectiveness of distributing limited medical resources [63].”

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Authors
Blasimme, A., & Vayena, E.
Affiliations
ETH Zurich (CH)
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2019
Pages
703-718
ISSN
1556-5068
OpenAlex
W3121892092
Cited by
48
References
1
Citations by year
2026: 9 · 2025: 9 · 2024: 10 · 2023: 6 · 2022: 5 · 2021: 5 · 2020: 3 · 2019: 1
FWCI
3.22
Type
book chapter
Language
en
Open access
Locations
  • Oxford University Press eBooks (publishedVersion)
  • SSRN Electronic Journal (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 in Clinical Research
Keywords
AI ethics, artificial intelligence in healthcare, biomedical research ethics, systemic governance, research ethics committees, clinical validation of AI, public health, disease surveillance, health promotion, regulatory framework, reflexivity

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.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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