The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.
Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement
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Citations
Cites
QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies
Whiting, P. F., Rutjes, A. W. S., Westwood, M. E., Mallett, S., Deeks, J. J., Reitsma, J. B., Leeflang, M. M. G., Sterne, J. A. C., Bossuyt, P. M. M., & the QUADAS-2 Group* (2011) · Annals of Internal Medicine · doi:10.7326/0003-4819-155-8-201110180-00009 · Cited by 14,199
Radiomics: Images Are More than Pictures, They Are Data
Gillies, R. J., Kinahan, P. E., & Hricak, H. (2016) · Radiology · doi:10.1148/radiol.2015151169 · Cited by 8,421
Radiomics: the bridge between medical imaging and personalized medicine
Lambin, P., Leijenaar, R. T. H., Deist, T. M., Peerlings, J., de Jong, E. E. C., van Timmeren, J., Sanduleanu, S., Larue, R. T. H. M., Even, A. J. G., Jochems, A., et al. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.141 · Cited by 5,688
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Aerts, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Carvalho, S., Bussink, J., Monshouwer, R., Haibe-Kains, B., Rietveld, D., et al. (2014) · Nature Communications · doi:10.1038/ncomms5006 · Cited by 5,132
Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)
McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/dji237 · Cited by 2,162
Huang, Y.-Q., Liang, C.-H., He, L., Tian, J., Liang, C.-S., Chen, X., Ma, Z.-L., & Liu, Z.-Y. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2015.65.9128 · Cited by 1,765
Sun, R., Limkin, E. J., Vakalopoulou, M., Dercle, L., Champiat, S., Han, S. R., Verlingue, L., Brandao, D., Lancia, A., Ammari, S., et al. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30413-3 · Cited by 1,236
Central challenges facing the national clinical research enterprise
Sung, N. S., Crowley, W. F., Genel, M., Salber, P., Sandy, L., Sherwood, L. M., Johnson, S. B., Catanese, V., Tilson, H., Getz, K., et al. (2003) · JAMA · doi:10.1001/jama.289.10.1278 · Cited by 1,235
Imaging biomarker roadmap for cancer studies
O'Connor, J. P. B., Aboagye, E. O., Adams, J. E., Aerts, H. J. W. L., Barrington, S. F., Beer, A. J., Boellaard, R., Bohndiek, S. E., Brady, M., Brown, G., et al. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.162 · Cited by 1,091
Cited by
Radiomics in medical imaging—“how-to” guide and critical reflection
van Timmeren, J. E., Cester, D., Tanadini-Lang, S., Alkadhi, H., & Baessler, B. (2020) · Insights into Imaging · doi:10.1186/s13244-020-00887-2 · Cited by 1,316
Predicting cancer outcomes with radiomics and artificial intelligence in radiology
Bera, K., Braman, N., Gupta, A., Velcheti, V., & Madabhushi, A. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-021-00560-7 · Cited by 819
Scapicchio, C., Gabelloni, M., Barucci, A., Cioni, D., Saba, L., & Neri, E. (2021) · La radiologia medica · doi:10.1007/s11547-021-01389-x · Cited by 435
Understanding Sources of Variation to Improve the Reproducibility of Radiomics
Zhao, B. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.633176 · Cited by 158
Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges
Stanzione, A., Cuocolo, R., Ugga, L., Verde, F., Romeo, V., Brunetti, A., & Maurea, S. (2022) · Cancers · doi:10.3390/cancers14194871 · Cited by 64
Metadata
- Authors
- Park, J. E., Kim, D., Kim, H. S., Park, S. Y., Kim, J. Y., Cho, S. J., Shin, J. H., & Kim, J. H.
- Venue
- European Radiology
- Published
- 2019-07-26
- Volume
- 30
- Issue
- 1
- Pages
- 523-536
- ISSN
- 0938-7994 (ISSN-L)
- 1432-1084
- OpenAlex
- W2965399740
- Cited by
- 282
- References
- 91
- FWCI
- 20.70
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement. https://app.cochat.ai/papers/10.1007/s00330-019-06360-z
- The paper
- Park, J. E., Kim, D., Kim, H. S., Park, S. Y., Kim, J. Y., Cho, S. J., Shin, J. H., & Kim, J. H. (2020). Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement. European Radiology. https://doi.org/10.1007/s00330-019-06360-z
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.
