
Yufeng Li
Articles
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Oct 7, 2024 |
bmccancer.biomedcentral.com | Wei Xiong |Ya Xie |Dong Wang |Xiaozhi Huang |Xiaohui Hao |Jianming Liu | +5 more
The present study received ethical approval from the Ethics Committee of Tangshan People’s Hospital (No. RMYY-LLKS-2021-017; Hebei, China). Prior to their participation, written informed consent was obtained from all patients. Esophageal cancer tissue samples were acquired from 65 patients diagnosed with primary esophageal squamous cell carcinoma during endoscopic biopsy at Tangshan People’s Hospital between January 2010 and December 2016.
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Aug 7, 2024 |
mdpi.com | Yue Ma |Hui Li |Yufeng Li |Dong Wei
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Apr 12, 2024 |
arxiv.org | Yufeng Li |Xu Yan |Min Gao |Weimin Wang
Research on the Application of Semantic Network in Disease Diagnosis Prompts Based on Medical Corpus
Mar 1, 2024 |
ijircst.org | Yufeng Li |Weimin Wang |Xu Yan |Min Gao
Yufeng Li , Weimin Wang, Xu Yan, Min Gao, MingXuan Xiao Abstract Portion of the causes of medical errors in outpatient clinics are incorrect treatment resulting from misdiagnosis. Misdiagnosis between diseases is often caused by similar and indistinguishable symptoms. Currently, disease knowledge and related symptom words that are prone to misdiagnosis are scattered in various medical literature or open online databases.
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Feb 12, 2024 |
ijircst.org | Weimin Wang |Yufeng Li |Xu Yan
Weimin WANG , Yufeng LI, Xu YAN, Mingxuan XIAO, Min GAO Abstract Deep learning technology have been broadly used in segmentation tasks of liver. To address the limitation of suboptimal segmentation for small targets, an end-to-end EAS(ECA-Attention and Separable convolution) U-Net is proposed based on deep learning.
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