Cited by 639Artificial Intelligence in HealthcarePrivacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Uniqueness of medical data mining

Cios, Krzysztof J., William Moore, G.·2002·Artificial Intelligence in Medicine

Abstract

This article addresses the special features of data mining with medical data. Researchers in other fields may not be aware of the particular constraints and difficulties of the privacy-sensitive, heterogeneous, but voluminous data of medicine. Ethical and legal aspects of medical data mining are discussed, including data ownership, fear of lawsuits, expected benefits, and special administrative issues. The mathematical understanding of estimation and hypothesis formation in medical data may be fundamentally different than those from other data collection activities. Medicine is primarily directed at patient-care activity, and only secondarily as a research resource; almost the only justification for collecting medical data is to benefit the individual patient. Finally, medical data have a special status based upon their applicability to all people; their urgency (including life-or-death); and a moral obligation to be used for beneficial purposes.

Integrity signals

Registry

Crossref · 10.1016/s0933-3657(02)00049-0

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Cios, K. J., & William Moore, G.
Affiliations
University of Colorado Boulder (US)
Corresponding author
Cios, Krzysztof J.
Venue
Artificial Intelligence in Medicine
Publisher
Elsevier BV
Published
2002-09
Volume
26
Issue
1-2
Pages
1-24
ISSN
0933-3657 (ISSN-L)
OpenAlex
W2043606064
Cited by
639
References
44
Citations by year
2026: 4 · 2025: 9 · 2024: 15 · 2023: 24 · 2022: 24 · 2021: 30 · 2020: 34 · 2019: 31 · 2018: 35 · 2017: 27 · 2016: 43 · 2015: 55 · 2014: 41 · 2013: 44 · 2012: 45
FWCI
25.42
Type
journal article
Language
en
Open access
closed
Locations
  • Artificial Intelligence in Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
medical data mining, privacy, ethical considerations, legal issues, data ownership, litigation risk, patient care, hypothesis generation, data heterogeneity, data volume
MeSH terms
Ethics, Medical, Humans, Information Storage and Retrieval, Medical Records Systems, Computerized, Computer Security, Patient-Centered Care

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.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review