The DOI matches its Crossref record; the references it cites are not checked yet.
Clinical and Histological Characteristics of Localized Morphea, Generalized Morphea and Systemic Sclerosis: A Comparative Study Aided by Machine Learning
Open accessAbstract
Abstract is missing (Short communication)
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.
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?
A random forest model distinguished 181 patients with localized morphea, generalized morphea, and systemic sclerosis, with top differentiating features including anticentromere autoantibodies, anti-scl-70 autoantibodies, rheumatoid factor, histologic sclerosis, and noncutaneous manifestations.
“Choi et al (2023) trained a random forest model, distinguishing 181 patients with localized morphea, generalized morphea, and systemic sclerosis (SSc), with top differentiating features (through SHAP) including anticentromere autoantibodies, anti—scl-70 autoantibodies, rheumatoid factor, histologic sclerosis, and noncutaneous manifestations.”
From Artificial intelligence–enabled precision medicine for inflammatory skin diseases (2026) · cites this paper as Choi et al, 2023
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
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
The citation lists haven’t been fetched yet
References 14 · Cited by 5
Research works printed but not linked: 28
- Kim J, Chung KB, Lee YI, Kim J, Lee JH. Clinical characteristics and histopathologic changes of morphea: a single-center, retrospective study of 137 patients. J Am Acad Dermatol 2021; 85: 105-113. · DOI
- https://doi.org/10.1016/j.jaad.2020.11.006 · DOI
- Knobler R, Moinzadeh P, Hunzelmann N, Kreuter A, Cozzio A, Mouthon L, et al. European Dermatology Forum S1-guideline on the diagnosis and treatment of sclerosing diseases of the skin, Part 1: localized scleroderma, systemic sclerosis and overlap syndromes. J Eur Acad Dermatol Venereol 2017; 31: 1401-1424. · DOI
- https://doi.org/10.1111/jdv.14458 · DOI
- Prasad S, Zhu JL, Schollaert-Fitch K, Torok KS, Jacobe HT. An evaluation of the performance of current morphea subtype classifications. JAMA Dermatol 2021; 157: 1-8. · DOI
- https://doi.org/10.1001/jamadermatol.2020.5809 · DOI
- LeRoy EC, Medsger TA, Jr. Criteria for the classification of early systemic sclerosis. J Rheumatol 2001; 28: 1573-1576.
- van den Hoogen F, Khanna D, Fransen J, Johnson SR, Baron M, Tyndall A, et al. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League against Rheumatism collaborative initiative. Arthritis Rheum 2013; 65: 2737-2747. · DOI
- https://doi.org/10.1002/art.38098 · DOI
- Walker D, Susa JS, Currimbhoy S, Jacobe H. Histopathological changes in morphea and their clinical correlates: results from the morphea in adults and children cohort V. J Am Acad Dermatol 2017; 76: 1124-1130. · DOI
- https://doi.org/10.1016/j.jaad.2016.12.020 · DOI
- Verrecchia F, Laboureau J, Verola O, Roos N, Porcher R, Bruneval P, et al. Skin involvement in scleroderma - where histological and clinical scores meet. Rheumatology (Oxford) 2007; 46: 833-841. · DOI
- https://doi.org/10.1093/rheumatology/kel451 · DOI
- Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP. SMOTE: synthetic minority over-sampling technique. Journal of artificial intelligence research 2002; 16: 321-357. · DOI · Paper page
- https://doi.org/10.1613/jair.953 · DOI · Paper page
- Tomek I. Two modifications of CNN. IEEE Trans Syst Man Cybern 1976; 6: 769-772. · DOI
- https://doi.org/10.1109/TSMC.1976.4309452 · DOI
- Batista GE, Prati RC, Monard MC. A study of the behavior of several methods for balancing machine learning training data. ACM SIGKDD Explorations Newsletter 2004; 6: 20-29. · DOI
- https://doi.org/10.1145/1007730.1007735 · DOI
- Opitz D, Maclin R. Popular ensemble methods: an empirical study. J AI Res 1999; 11: 169-198. · DOI · Paper page
- https://doi.org/10.1613/jair.614 · DOI · Paper page
- Lundberg SM, Lee S-I. A unified approach to interpreting model predictions. Adv Neural Inf Process Syst 2017; 30.
- Succaria F, Kurban M, Kibbi AG, Abbas O. Clinicopathological study of 81 cases of localized and systemic scleroderma. J Eur Acad Dermatol Venereol 2013; 27: e191-196. · DOI
- https://doi.org/10.1111/j.1468-3083.2012.04581.x · DOI
- Torres JE, Sanchez JL. Histopathologic differentiation between localized and systemic scleroderma. Am J Dermatopathol 1998; 20: 242-245. · DOI
- https://doi.org/10.1097/00000372-199806000-00003 · DOI
- Laxer RM, Zulian F. Localized scleroderma. Curr Opin Rheumatol 2006; 18: 606-613. · DOI
- https://doi.org/10.1097/01.bor.0000245727.40630.c3 · DOI
Metadata
- Authors
- Choi, S., Kim, J., Lee, J. H., Lee, Y. N., & Lee, J. H.
- Affiliations
- Yonsei University (KR)
- Corresponding author
- Lee, Ju Hee
- Venue
- Acta Dermato-Venereologica
- Publisher
- Medical Journals Sweden AB
- Published
- 2023-09-20
- Volume
- 103
- Pages
- adv11953
- ISSN
- 0001-5555 (ISSN-L)
- 1651-2057
- PMC
- PMC10522325
- OpenAlex
- W4386889347
- Cited by
- 5
- References
- 14
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2
- FWCI
- 1.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Acta Dermato Venereologica (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Korea Medical Device Development Fund
- Ministry of Trade, Industry and Energy
- Ministry of Food and Drug Safety
- Ministry of Science and ICT, South Korea
- Topics
- Health Sciences › Medicine › Rheumatology › Systemic Sclerosis and Related Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Connective tissue disorders research
- Health Sciences › Medicine › Dermatology › Dermatologic Treatments and Research
- Keywords
- generalized morphea, systemic sclerosis, clinical features, histological characteristics, machine learning classification, differential diagnosis
- MeSH terms
- Machine Learning, Humans, Scleroderma, Localized, Scleroderma, Systemic
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
