机构

• 自动化研究所 [43]

采集方式

• OAI收割 [43]

内容类型

• 期刊论文 [42]
• 会议论文 [1]

发表日期

• 2023 [1]
• 2022 [3]
• 2021 [4]
• 2020 [8]
• 2019 [23]
• 2018 [3]
• 更多

学科主题

筛选

浏览/检索结果: 共43条，第1-10条 帮助 限定条件 专题：自动化研究所    第一署名单位    第一作者单位    通讯作者单位     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Radiomic signatures reveal multiscale intratumor heterogeneity associated with tissue tolerance and survival in re-irradiated nasopharyngeal carcinoma: a multicenter study 期刊论文  OAI收割 BMC MEDICINE, 2023, 卷号: 21, 期号: 1, 页码: 13 作者:  Liu, Ting;  Dong, Di;  Zhao, Xun;  Ou, Xiao-Min;  Yi, Jun-Lin   |  收藏  |  浏览/下载：13/0  |  提交时间：2024/02/22 Recurrent nasopharyngeal carcinoma  Re-radiotherapy  Nasopharyngeal necrosis  Radiomics   The pathological risk score: A new deep learning-based signature for predicting survival in cervical cancer 期刊论文  OAI收割 CANCER MEDICINE, 2022, 页码: 13 作者:  Chen, Chi;  Cao, Yuye;  Li, Weili;  Liu, Zhenyu;  Liu, Ping   |  收藏  |  浏览/下载：32/0  |  提交时间：2022/07/25 cervical cancer  deep learning  disease-free survival  overall survival  whole slide image   Deep learning with whole slide images can improve the prognostic risk stratification with III colorectal cancer 期刊论文  OAI收割 COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2022, 卷号: 221, 页码: 11 作者:  Sun, Caixia;  Li, Bingbing;  Wei, Genxia;  Qiu, Weihao;  Li, Danyi   |  收藏  |  浏览/下载：29/0  |  提交时间：2022/07/25 Chemotherapy duration  Whole slide images  Deep learning  Colorectal cancer  Prognosis   Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma 期刊论文  OAI收割 EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 页码: 11 作者:  Zhao, Xun;  Liang, Yu-Jing;  Zhang, Xu;  Wen, Dong-Xiang;  Fan, Wei   |  收藏  |  浏览/下载：45/0  |  提交时间：2022/06/10 Recurrent nasopharyngeal carcinoma  Survival analysis  Radiomics  Deep learning   Gene signatures predict biochemical recurrence-free survival in primary prostate cancer patients after radical therapy 期刊论文  OAI收割 CANCER MEDICINE, 2021, 页码: 11 作者:  Su, Qiang;  Liu, Zhenyu;  Chen, Chi;  Gao, Han;  Zhu, Yongbei   |  收藏  |  浏览/下载：23/0  |  提交时间：2021/11/03 biochemical recurrence-free survival  gene signature  LASSO-Cox regression  primary prostate cancer  radical therapy   A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study 期刊论文  OAI收割 EBIOMEDICINE, 2021, 卷号: 70, 页码: 10 作者:  Zhong, Lianzhen;  Dong, Di;  Fang, Xueliang;  Zhang, Fan;  Zhang, Ning   |  收藏  |  浏览/下载：40/0  |  提交时间：2021/11/03 Multi-task deep learning  Radiomic nomogram  Survival analysis  Treatment decision  Advanced nasopharyngeal carcinoma   Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients 期刊论文  OAI收割 NPJ PRECISION ONCOLOGY, 2021, 卷号: 5, 期号: 1, 页码: 9 作者:  Yan, Jing;  Zhang, Bin;  Zhang, Shuaitong;  Cheng, Jingliang;  Liu, Xianzhi   |  收藏  |  浏览/下载：31/0  |  提交时间：2021/11/02 CT-based radiomics to predict development of macrovascular invasion in hepatocellular carcinoma: A multicenter study 期刊论文  OAI收割 Hepatobiliary & Pancreatic Diseases International, 2021, 卷号: 2021, 期号: --, 页码: -- 作者:  Jingwei Wei;  Sirui Fu;  Jie Zhang;  Dongsheng Gu;  Xiaoqun Li   |  收藏  |  浏览/下载：12/0  |  提交时间：2022/04/06 Computed tomography  Hepatocellular carcinoma  Macrovascular invasion  Prognosis  Radiomics   Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer 期刊论文  OAI收割 NATURE COMMUNICATIONS, 2020, 卷号: 11, 期号: 1, 页码: 11 作者:  Liu, Zhenyu;  Meng, Xiaochun;  Zhang, Hongmei;  Li, Zhenhui;  Liu, Jiangang   |  收藏  |  浏览/下载：40/0  |  提交时间：2021/01/07 Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study 期刊论文  OAI收割 MEDICAL PHYSICS, 2020, 页码: 10 作者:  Wang, Siwen;  Feng, Caizhen;  Dong, Di;  Li, Hailin;  Zhou, Jing   |  收藏  |  浏览/下载：18/0  |  提交时间：2020/09/07 disease-free survival  gastric cancer  multidetector-row computed tomography  risk stratification  radiomics