The DOI matches its Crossref record.
Correction: An explainable hybrid deep learning framework for precise skin lesion segmentation and multi-class classification
Open accessAbstract
[This corrects the article DOI: 10.3389/fmed.2025.1681542.].
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Sonuç, E., Saihood, Q., Yargı Baydilli, Y., & Özcan, E. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1871689
Manoj, R. (2026) · Journal of Innovation and Technology · doi:10.61453/joit.v2026_0203
Hameed, S., Nauman, M. A., Hasnain, M., Mamoon, M., Afzal, Z., & Bukhari, K. (2026) · VFAST Transactions on Software Engineering · doi:10.21015/vtse.v14i2.2419
Abbas, F., & Naseer, I. (2026) · International Journal of Innovations in Science and Technology · doi:10.33411/ijist/2034
A Hybrid Vision Transformer Based Edge‐Guided Boundary Attention U‐Net for Skin Lesion Segmentation
Monika, M. C., & Shalini, R. B. (2026) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.70449
Metadata
- Authors
- Fiaz, M., Shoaib Khan, M. B., Khan, A. H., Bilal, A., Abdullah, M., Darem, A. A., & Sarwar, R.
- Affiliations
- University of Central Punjab (PK)
- Green International University (PK)
- Hainan Normal University (CN)
- University of Bisha (SA)
- Northern Border University (SA)
- Manchester Metropolitan University (GB)
- Corresponding author
- Sarwar, Raheem
- Venue
- Frontiers in Medicine
- Publisher
- Frontiers Media SA
- Published
- 2025-10-29
- Volume
- 12
- Pages
- 1724427-1724427
- ISSN
- 2296-858X (ISSN-L)
- PMC
- PMC12606669
- OpenAlex
- W4415665659
- Cited by
- 8
- References
- 0
- Citations by year
- 2026: 8
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Medicine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- e-space (Manchester Metropolitan University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- University of Bisha
- Northern Border University (NBU‐CRP‐2025‐2903)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- skin lesion segmentation, skin lesion classification, explainable deep learning, hybrid deep learning model, dermatology
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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: Correction: An explainable hybrid deep learning framework for precise skin lesion segmentation and multi-class classification. https://app.cochat.ai/papers/10.3389/fmed.2025.1724427
- The paper
- Fiaz, M., Shoaib Khan, M. B., Khan, A. H., Bilal, A., Abdullah, M., Darem, A. A., & Sarwar, R. (2025). Correction: An explainable hybrid deep learning framework for precise skin lesion segmentation and multi-class classification. Frontiers in Medicine. https://doi.org/10.3389/fmed.2025.1724427