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复旦大学上海医学院 [14]
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期刊论文 [29]
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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
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:23/0
  |  
提交时间:2022/12/27
Breast cancer
Neoadjuvant chemotherapy
Pathological complete response
Whole-slide image
Deep learning
Current status of total neoadjuvant therapy for locally advanced rectal cancer
期刊论文
ASIA-PACIFIC JOURNAL OF CLINICAL ONCOLOGY, 2021
作者:
Feng, Wei
;
Yu, Bin
;
Zhang, Zhenya
;
Li, Juan
;
Wang, Yuxiang
收藏
  |  
浏览/下载:50/0
  |  
提交时间:2022/01/10
chemoradiation therapy
chemotherapy
disease-free survival (DFS)
pathological complete response (pCR)
rectal cancer
sphincter preservation
Machine Learning-Based Radiomics Nomogram Using Magnetic Resonance Images for Prediction of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Patients
期刊论文
FRONTIERS IN ONCOLOGY, 2020, 卷号: 10
作者:
Chen, Shujun
;
Shu, Zhenyu
;
Li, Yongfeng
;
Chen, Bo
;
Tang, Lirong
收藏
  |  
浏览/下载:30/0
  |  
提交时间:2020/11/26
radiomics
nomogram
breast cancer
neoadjuvant chemotherapy
pathological complete response
machine learning
The role of the phosphatase and tensin homolog status in predicting pathological complete response to neoadjuvant anti-HER2 therapies in HER2-positive primary breast cancer A meta-analysis
期刊论文
MEDICINE, 2019, 卷号: 98, 期号: 5
作者:
Zhang, Chi
;
Guo, Ying
;
Li, Jiyu
;
Tian, Xingsong
;
Duan, Xuening
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2019/12/11
anti-HER2 agents
HER2-positive breast cancer
meta-analysis
neoadjuvant treatment
pathological complete response
PTEN
Developing a prediction model based on MRI for pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer
期刊论文
2019, 卷号: 44, 期号: 9,SI, 页码: 2978-2987
作者:
Wan, Lijuan
;
Zhang, Chongda
;
Zhao, Qing
;
Meng, Yankai
;
Zou, Shuangmei
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2020/01/03
Rectal neoplasms
Magnetic resonance imaging
Magnetic resonance tumor regression grading
Neoadjuvant chemoradiotherapy
Pathological complete response
Concomitant dose escalation with image-guided Tomotherapy in locally advanced mid-low rectal cancer: a single-center study
期刊论文
2019, 卷号: 11, 页码: 1579-1586
作者:
Zhao, Jing
;
Liu, Xiaoliang
;
Wang, Weiping
;
Hu, Ke
;
Zhang, Fuquan
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2020/01/03
rectal cancer
neoadjuvant chemoradiotherapy
dose escalation
pathological complete response
Tomotherapy
Efficacy of two-weekly nanoparticle albumin-bound paclitaxel as neoadjuvant chemotherapy for breast cancer
期刊论文
2019, 卷号: 14, 期号: 12, 页码: 1595-1603
作者:
Xie, Fei
;
Chen, Rui
;
Zhang, Ling
;
Yin, Zinan
;
Zhu, Qiannan
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2020/01/03
breast cancer
nanoparticle albumin-bound paclitaxel
neoadjuvant chemotherapy
pathological complete response
Clinical significance of quantitative HER2 gene amplification as related to its predictive value in breast cancer patients in neoadjuvant setting
期刊论文
ONCOTARGETS AND THERAPY, 2018, 卷号: 11
作者:
Zhou, Liheng
;
Wu, Ziping
;
Xu, Shuguang
;
Yin, Wenjin
;
Lin, Yanpin
收藏
  |  
浏览/下载:48/0
  |  
提交时间:2019/12/05
breast cancer
neoadjuvant
quantitative HER2 gene amplification
pathological complete response
predictive
Predictive value of tumor-infiltrating lymphocytes to pathological complete response in neoadjuvant treated triple-negative breast cancers
期刊论文
DIAGNOSTIC PATHOLOGY, 2018, 卷号: 13
作者:
Ruan, Miao
;
Tian, Tian
;
Rao, Jia
;
Xu, Xiaoli
;
Yu, Baohua
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2019/12/05
Tumor-infiltrating lymphocytes
Breast cancer
Triple-negative
Pathological complete response
Predictive factor
Impact of pathological complete response following neoadjuvant chemoradiotherapy in esophageal cancer
期刊论文
JOURNAL OF THORACIC DISEASE, 2018, 卷号: 10, 期号: 7
作者:
Soror, Tamer
;
Kho, Gerlinda
;
Zhao, Kuai-Le
;
Ismail, Mahmoud
;
Badakhshi, Harlin
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/05
Pathological complete response (pCR)
neoadjuvant treatment
neoadjuvant radiochemotherapy (nRCT)
esophageal cancer
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