Development and validation of the MRI-based deep learning classifier for distinguishing perianal fistulizing Crohn’s disease from cryptoglandular fistula: a multicenter cohort study

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Publication Details

Journal
EClinicalMedicine
Published
2024-11-21
DOI
https://doi.org/10.1016/j.eclinm.2024.102940
Citations
5
Primary Topic
Anorectal Disease Treatments and Outcomes
Type
article
Field-Weighted Citation Impact
2.86

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article

Development and validation of the MRI-based deep learning classifier for distinguishing perianal fistulizing Crohn’s disease from cryptoglandular fistula: a multicenter cohort study

Bolin Yang, Ke Deng, Xiaochun Meng, Jiaying Yao et al.
5 citations
EClinicalMedicine
Anorectal Disease Treatments and Outcomes
2.86
article

Development and validation of the MRI-based deep learning classifier for distinguishing perianal fistulizing Crohn’s disease from cryptoglandular fistula: a multicenter cohort study

Bolin Yang, Ke Deng, Xiaochun Meng, Jiaying Yao, Wenjun Li, Juan Li, Tao Chen, Yuhuan Lin, Jun Luo, Donglin Ren, Hongcheng Lin, Lanlan Li, Heng Zhang
article en
5 citations

Abstract

No abstract available for this paper.
EClinicalMedicineVol. 78
Nanjing University of Chinese Medicine (CN), Sun Yat-sen University (CN), Sixth Affiliated Hospital of Sun Yat-sen University (CN), Panyu District Central Hospital (CN), Fuzhou University (CN)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 9%
Anorectal Disease Treatments and Outcomes
2.86
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Development and validation of the MRI-based deep learning classifier for distinguishing perianal fistulizing Crohn’s disease from cryptoglandular fistula: a multicenter cohort study — Bolin Yang, Ke Deng, et al. · EClinicalMedicine (2024) | TGRS Research Map | TGRS