机构

• 自动化研究所 [12]
• 地理科学与资源研究所 [1]
• 数学与系统科学研究院 [1]
• 上海药物研究所 [1]
• 广州能源研究所 [1]
• 紫金山天文台 [1]
• 更多

采集方式

• OAI收割 [17]

内容类型

• 期刊论文 [17]

发表日期

• 2023 [3]
• 2022 [5]
• 2021 [1]
• 2020 [6]
• 2019 [2]

学科主题

筛选

浏览/检索结果: 共17条，第1-10条 帮助 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 Tumor Mutation Burden-Related Histopathologic Features for Predicting Overall Survival in Gliomas Using Graph Deep Learning 期刊论文  OAI收割 AMERICAN JOURNAL OF PATHOLOGY, 2023, 卷号: 193, 期号: 12, 页码: 2111-2121 作者:  Sun, Caixia;  Luo, Tao;  Liu, Zhenyu;  Ge, Jia;  Shao, Lizhi   |  收藏  |  浏览/下载：5/0  |  提交时间：2024/02/22 MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer 期刊论文  OAI收割 JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE B, 2023, 卷号: 24, 期号: 8, 页码: 663-681 作者:  Zhu, Xuehua;  Shao, Lizhi;  Liu, Zhenyu;  Liu, Zenan;  He, Jide   |  收藏  |  浏览/下载：6/0  |  提交时间：2023/11/17 Magnetic resonance imaging (MRI)  Radiomics  Prostate cancer  Predictive model   Afforestation vegetation uses water from very deep soil layers in the semi-arid Loess Plateau 期刊论文  OAI收割 HYDROLOGICAL PROCESSES, 2023, 卷号: 37, 期号: 7, 页码: e14933 作者:  Wu, Yuanzhi;  Jia, Xiaoxu;  An, Juan;  Huang, Laiming;  Wang, Lizhi   |  收藏  |  浏览/下载：12/0  |  提交时间：2023/08/22 dual stable isotopes  Loess Plateau  MixSIAR  soil dried layer  water uptake pattern   Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer : A multicenter study 期刊论文  OAI收割 BREAST, 2022, 卷号: 66, 页码: 183-190 作者:  Li, Bao;  Li, Fengling;  Liu, Zhenyu;  Xu, FangPing;  Ye, Guolin   |  收藏  |  浏览/下载：31/0  |  提交时间：2022/12/27 Breast cancer  Neoadjuvant chemotherapy  Pathological complete response  Whole-slide image  Deep learning   Patient-level grading prediction of prostate cancer from mp-MRI via GMINet 期刊论文  OAI收割 COMPUTERS IN BIOLOGY AND MEDICINE, 2022, 卷号: 150, 页码: 10 作者:  Shao, Lizhi;  Liu, Zhenyu;  Liu, Jiangang;  Yan, Ye;  Sun, Kai   |  收藏  |  浏览/下载：36/0  |  提交时间：2022/11/21 mp-MRI  Prostate cancer  Grade group  Patient-level prediction  Deep learning   Anti-inflammatory sesquiterpenoid dimers from Artemisia atrovirens 期刊论文  OAI收割 FITOTERAPIA, 2022, 卷号: 159, 页码: 10 作者:  Shao, Zhengguang;  Li, Lizhi;  Zheng, Yongzhe;  Gong, Qi;  Ke, Chang-Qiang   |  收藏  |  浏览/下载：24/0  |  提交时间：2022/08/16 Artemisia atrovirens  Sesquiterpenoid dimer  Guaianolide  TDDFT ECD calculation  Artatrovirenolides A-H   A two-center radiomic analysis for differentiating major depressive disorder using multi-modality MRI data under different parcellation methods 期刊论文  OAI收割 JOURNAL OF AFFECTIVE DISORDERS, 2022, 卷号: 300, 页码: 1-9 作者:  Sun, Kai;  Liu, Zhenyu;  Chen, Guanmao;  Zhou, Zhifeng;  Zhong, Shuming   |  收藏  |  浏览/下载：38/0  |  提交时间：2022/02/16 Major depressive disorder  rs-fMRI  VBM  Radiomics  Classification   Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study 期刊论文  OAI收割 LANCET DIGITAL HEALTH, 2022, 卷号: 4, 期号: 1, 页码: E8-E17 作者:  Feng, Lili;  Liu, Zhenyu;  Li, Chaofeng;  Li, Zhenhui;  Lou, Xiaoying   |  收藏  |  浏览/下载：21/0  |  提交时间：2022/02/16 Patient-Level Prediction of Multi-Classification Task at Prostate MRI Based on End-to-End Framework Learning From Diagnostic Logic of Radiologists 期刊论文  OAI收割 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2021, 卷号: 68, 期号: 12, 页码: 3690-3700 作者:  Shao, Lizhi;  Liu, Zhenyu;  Yan, Ye;  Liu, Jiangang;  Ye, Xiongjun   |  收藏  |  浏览/下载：26/0  |  提交时间：2021/12/28 Magnetic resonance imaging  Principal component analysis  Pathology  Lesions  Optimization  Task analysis  Predictive models  Gleason score  prostate cancer  patient-level prediction  joint optimization  MRI  reinforcement learning   Improving initial nodal staging of T3 rectal cancer using quantitative image features 期刊论文  OAI收割 BRITISH JOURNAL OF SURGERY, 2020, 页码: 2 作者:  Zhou, Xuezhi;  Liu, Zhenyu;  Zhang, Dafu;  Wu, Lin   |  收藏  |  浏览/下载：24/0  |  提交时间：2020/09/28