日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Primary tumor-derived, multiparametric MRI-based deep learning-radiomics-clinical model for predicting lymph node metastasis in early-stage cervical cancer

基于原发肿瘤的多参数磁共振成像深度学习-放射组学-临床模型预测早期宫颈癌淋巴结转移

Bao, Yu Hao; Chen, Yan; Xiao, Mei Ling; Li, Yong Ai; Ma, Feng Hua; Li, Hai Ming; Wu, Jing Yan; Zhang, Guo Fu; Qiang, Jin Wei

L-arginine from elder human mesenchymal stem cells induces angiogenesis and enhances therapeutic effects on ischemic heart diseases.

来自老年人类间充质干细胞的L-精氨酸可诱导血管生成,并增强对缺血性心脏病的治疗效果

Li Jian-Zhong, Zhan Xu, Sun Hao-Bo, Chi Chao, Zhang Guo-Fu, Liu Dong-Hui, Zhang Wen-Xi, Sun Li-Hua, Kang Kai

Sutureless total arch replacement in patients with acute type A aortic dissection

急性A型主动脉夹层患者的无缝线全弓置换术

Qiu, Dong-Yun; Zhu, Er-Jun; Li, Yong-Tao; Xue, Yang-Hong; Zhang, Hai-Tao; Sun, Bo; Chi, Chao; Meng, Wei-Xin; Zhang, Guo-Fu; Xu, Lei; Pan, Hao-Dong; Wang, Hanghang; Pan, Tuo; Xie, Bao-Dong

The deep learning radiomics nomogram helps to evaluate the lymph node status in cervical adenocarcinoma/adenosquamous carcinoma

深度学习放射组学列线图有助于评估宫颈腺癌/腺鳞癌的淋巴结状态。

Xiao, Mei Ling; Fu, Le; Qian, Ting; Wei, Yan; Ma, Feng Hua; Li, Yong Ai; Cheng, Jie Jun; Qian, Zhao Xia; Zhang, Guo Fu; Qiang, Jin Wei

Magnetic resonance imaging for distinguishing ovarian clear cell carcinoma from high-grade serous carcinoma

磁共振成像用于鉴别卵巢透明细胞癌和高级别浆液性癌

Ma, Feng-Hua; Qiang, Jin-Wei; Zhang, Guo-Fu; Li, Hai-Ming; Cai, Song-Qi; Rao, Ya-Min

Intravoxel incoherent motion diffusion-weighted imaging in differentiating uterine fibroid from focal adenomyosis: initial results

体素内不相干运动扩散加权成像在鉴别子宫肌瘤和局灶性子宫腺肌症中的应用:初步结果

Tian, Tao; Zhang, Guo-Fu; Zhang, He; Liu, Hui

Effect of low-frequency rTMS on aphasia in stroke patients: a meta-analysis of randomized controlled trials

低频重复经颅磁刺激对卒中患者失语症的影响:一项随机对照试验的荟萃分析

Ren, Cai-Li; Zhang, Guo-Fu; Xia, Nan; Jin, Chun-Hui; Zhang, Xiu-Hua; Hao, Jian-Feng; Guan, Hong-Bo; Tang, Hong; Li, Jian-An; Cai, De-Liang

Value of 3.0 T diffusion-weighted imaging in discriminating thecoma and fibrothecoma from other adnexal solid masses

3.0T弥散加权成像在鉴别卵泡膜瘤和纤维卵泡膜瘤与其他附件实性肿块方面的价值

Zhang, He; Zhang, Guo-Fu; Wang, Tian-Ping; Zhang, Hao

Ovarian Sertoli-Leydig cell tumors: MRI findings and pathological correlation

卵巢支持细胞-间质细胞瘤:MRI表现及病理相关性

Cai, Song-Qi; Zhao, Shu-Hui; Qiang, Jin-Wei; Zhang, Guo-Fu; Wang, Xue-Zhen; Wang, Li

Evaluation of primary adnexal masses by 3T MRI: categorization with conventional MR imaging and diffusion-weighted imaging

3T MRI对原发性附件肿块的评估:与常规磁共振成像和弥散加权成像的分类

Zhang, He; Zhang, Guo-Fu; He, Zhi-Yan; Li, Zheng-Yu; Zhu, Ming; Zhang, Gui-Xiang