Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Enming Cui"'
Autor:
Bao Feng, Jiangfeng Shi, Liebin Huang, Zhiqi Yang, Shi-Ting Feng, Jianpeng Li, Qinxian Chen, Huimin Xue, Xiangguang Chen, Cuixia Wan, Qinghui Hu, Enming Cui, Yehang Chen, Wansheng Long
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024)
Abstract The prediction of patient disease risk via computed tomography (CT) images and artificial intelligence techniques shows great potential. However, training a robust artificial intelligence model typically requires large-scale data support. In
Externí odkaz:
https://doaj.org/article/c3540e73f2b44e58a2d13a834e22bd15
Autor:
Bao Feng, Changyi Ma, Yu liu, Qinghui Hu, Yan Lei, Meiqi Wan, Fan Lin, Jin Cui, Wansheng Long, Enming Cui
Publikováno v:
Heliyon, Vol 10, Iss 3, Pp e25655- (2024)
Background: Differentiating adrenal adenomas from metastases poses a significant challenge, particularly in patients with a history of extra-adrenal malignancy. This study investigates the performance of three-phase computed tomography (CT) based rob
Externí odkaz:
https://doaj.org/article/843933f1b6bf49dc9f7b0bde0be377c3
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
ObjectivesIn patients with hepatocellular carcinoma (HCC), accurately predicting the preoperative microvascular invasion (MVI) status is crucial for improving survival rates. This study proposes a multi-modal domain-adaptive fusion model based on dee
Externí odkaz:
https://doaj.org/article/654047c53f8740bfbf8d86ed8bce1dce
Autor:
Xuehua Li, Naiwen Zhang, Cicong Hu, Yuqin Lin, Jiaqiang Li, Zhoulei Li, Enming Cui, Li Shi, Xiaozhao Zhuang, Jianpeng Li, Jiahang Lu, Yangdi Wang, Renyi Liu, Chenglang Yuan, Haiwei Lin, Jinshen He, Dongping Ke, Shanshan Tang, Yujian Zou, Bo He, Canhui Sun, Minhu Chen, Bingsheng Huang, Ren Mao, Shi-Ting Feng
Publikováno v:
EClinicalMedicine, Vol 56, Iss , Pp 101805- (2023)
Summary: Background: Visceral adipose tissue (VAT) is involved in the pathogenesis of Crohn's disease (CD). However, data describing its effects on CD progression remain scarce. We developed and validated a VAT-radiomics model (RM) using computed tom
Externí odkaz:
https://doaj.org/article/7396d9dbc1884f26858d37a0a1537ab4
Autor:
Yu Liu, Enming Cui
Publikováno v:
Frontiers in Human Neuroscience, Vol 16 (2022)
Preoperative diagnosis of gastric cancer and primary gastric lymphoma is challenging and has important clinical significance. Inspired by the inductive reasoning learning of the human brain, transfer learning can improve diagnosis performance of targ
Externí odkaz:
https://doaj.org/article/c23d7882e2bf4462850d1c3904d8f671
Autor:
Bao Feng, Zhuangsheng Liu, Yu Liu, Yehang Chen, Haoyang Zhou, Enming Cui, Xiaoping Li, Xiangmeng Chen, Ronggang Li, Tianyou Yu, Ling Zhang, Wansheng Long
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
ObjectiveTo compare the performance of abbreviated breast magnetic resonance imaging (AB-MRI)-based transfer learning (TL) algorithm and radionics analysis for lymphovascular invasion (LVI) prediction in patients with clinically node-negative invasiv
Externí odkaz:
https://doaj.org/article/f15ba0272a3243818898ecc92328459a
Autor:
Xiangmeng Chen, Bao Feng, Yehang Chen, Kunfeng Liu, Kunwei Li, Xiaobei Duan, Yixiu Hao, Enming Cui, Zhuangsheng Liu, Chaotong Zhang, Wansheng Long, Xueguo Liu
Publikováno v:
Cancer Imaging, Vol 20, Iss 1, Pp 1-13 (2020)
Abstract Purpose To develop a radiomics nomogram based on computed tomography (CT) images that can help differentiate lung adenocarcinomas and granulomatous lesions appearing as sub-centimeter solid nodules (SCSNs). Materials and methods The records
Externí odkaz:
https://doaj.org/article/8eca30130b16477fa8c92908ce4b4c53
Autor:
Tao Zhou, Jian Guan, Bao Feng, Huimin Xue, Jin Cui, Qionglian Kuang, Yehang Chen, Kuncai Xu, Fan Lin, Enming Cui, Wansheng Long
Publikováno v:
European Radiology. 33:4323-4332
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4642e4976e414ec1cde44626d7056546
https://doi.org/10.1007/s00330-022-09384-0
https://doi.org/10.1007/s00330-022-09384-0
Publikováno v:
Journal of Magnetic Resonance Imaging. 54:1212-1221
BACKGROUND Accurate evaluation of the invasion depth of tumors with a Vesical Imaging-Reporting and Data System (VI-RADS) score of 3 is difficult. PURPOSE To evaluate the diagnostic performance of a new magnetic resonance imaging (MRI) strategy based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca3c686729557444f0627130e54cee21
https://doi.org/10.1002/jmri.27676
https://doi.org/10.1002/jmri.27676
Publikováno v:
Abdominal Radiology. 46:3866-3876
To develop and externally validate a multiphase computed tomography (CT)-based machine learning (ML) model for staging liver fibrosis (LF) by using whole liver slices. The development dataset comprised 232 patients with pathological analysis for LF,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86fb726b45c70c52d1d1c19d8cc70ebc
https://doi.org/10.1007/s00261-021-03051-6
https://doi.org/10.1007/s00261-021-03051-6