The DOI matches its Crossref record.
ROC Analysis Applied to the Evaluation of Medical Imaging Techniques
Abstract
Analysis in terms of the relative operating characteristic (ROC) has recently been applied to several studies of medical decision-making, primarily to decisions based on imaging techniques. This paper presents a brief description of the ROC, and shows how it provides a measure of diagnostic accuracy that is free of judgmental bias. The results of medical studies are reviewed, and the main questions of theory and method that have arisen in the medical context are identified. Certain of these questions are basic to any psychophysical test, in which case an attempt has been made to present the best available answers. Other questions are of special medical importance and relevant reports are reviewed along with a description of current efforts to provide answers.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Measuring the Accuracy of Diagnostic Systems
Swets, J. A. (1988) · Science · doi:10.1126/science.3287615 · Cited by 10,058
Self-citationThe use of the area under the ROC curve in the evaluation of machine learning algorithms
Bradley, A. P. (1997) · Pattern Recognition · doi:10.1016/s0031-3203(96)00142-2 · Cited by 7,217
Hanley, J. A., & McNeil, B. J. (1983) · Radiology · doi:10.1148/radiology.148.3.6878708 · Cited by 7,016
(2013) · Europe PMC (PubMed Central) · Cited by 2,089
Metadata
- Authors
- SWETS, J. A.
- Venue
- Investigative Radiology
- Published
- 1979-03
- Volume
- 14
- Issue
- 2
- Pages
- 109-121
- ISSN
- 0020-9996 (ISSN-L)
- OpenAlex
- W2060136512
- Cited by
- 699
- References
- 0
- FWCI
- 7.85
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: ROC Analysis Applied to the Evaluation of Medical Imaging Techniques. https://app.cochat.ai/papers/10.1097/00004424-197903000-00002
- The paper
- SWETS, J. A. (1979). ROC Analysis Applied to the Evaluation of Medical Imaging Techniques. Investigative Radiology. https://doi.org/10.1097/00004424-197903000-00002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
