The DOI matches its Crossref record.
397 Distinction of Mycosis Fungoides From Its Morphologic Mimics Using AI-Powered Analysis of Whole Slide Images
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Claims the paper makes
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?
Preliminary reports of other unimodal H&E models, such as recent conference abstracts by Sharaf et al., have reported high accuracies, but these systems were evaluated on heavily restricted sample sizes, increasing the risk of overfitting relative to our large-scale, multicentre validation.
“Similarly, while preliminary reports of other unimodal H&E models, such as recent conference abstracts by Sharaf et al., have reported high accuracies, these systems were evaluated on heavily restricted sample sizes 19,20 , increasing the risk of overfitting relative to our large-scale, multicentre validation.”
Citations
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Doeleman, T., Brussee, S., Valkema, P. A., Kempf, W., Vermeer, M. H., Kers, J., Wynaendts, L. C. D., Kerckhoffs, K. G. P., de Jonge, M. M., Nguyen, A. H., et al. (2026) · medRxiv · doi:10.64898/2026.07.27.26359009
Metadata
- Authors
- Sharaf, M., Jour, G., Smoller, B., Giubellino, A., Shvartsbeyn, M., & Park, C.
- Affiliations
- New York University (US)
- NYU Langone Health (US)
- University of Rochester Medicine (US)
- University of Minnesota (US)
- Venue
- Laboratory Investigation
- Publisher
- Elsevier BV
- Published
- 2026-03
- Volume
- 106
- Issue
- 3
- Pages
- 104680
- ISSN
- 0023-6837 (ISSN-L)
- OpenAlex
- W7140095518
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Laboratory Investigation (publishedVersion)
- Topics
- Health Sciences › Medicine › Dermatology › Cutaneous lymphoproliferative disorders research
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- mycosis fungoides, cutaneous T-cell lymphoma, differential diagnosis, whole slide images, artificial intelligence, image analysis
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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