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Guiding induction chemotherapy of locoregionally advanced nasopharyngeal carcinoma with ternary classification of predicted individual treatment effect Journal article
Zhiying Liang, Kit Ian Kou, Chao Luo, Shuqi Li, Yuliang Zhu, Wenjie Huang, Di Cao, Yifei Liu, Guangying Ruan, Shaobo Liang, Xi Chen, Guoyi Zhang, Lizhi Liu, Haojiang Li. Guiding induction chemotherapy of locoregionally advanced nasopharyngeal carcinoma with ternary classification of predicted individual treatment effect[J]. Radiotherapy and Oncology, 2024, 201, 110571.
Authors:  Zhiying Liang;  Kit Ian Kou;  Chao Luo;  Shuqi Li;  Yuliang Zhu; et al.
Adobe PDF | Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.9/5.4 | Submit date：2024/10/16
Nasopharyngeal Carcinoma  Induction Chemotherapy  Overall Survival  Treatment Decision-making  Predicted Individual Treatment Effect  
Multimodal Machine Learning for Prognosis and Survival Prediction in Renal Cell Carcinoma Patients: A Two-Stage Framework with Model Fusion and Interpretability Analysis Journal article
Yan, Keyue, Fong, Simon, Li, Tengyue, Song, Qun. Multimodal Machine Learning for Prognosis and Survival Prediction in Renal Cell Carcinoma Patients: A Two-Stage Framework with Model Fusion and Interpretability Analysis[J]. APPLIED SCIENCES-BASEL, 2024, 14(13), 5686.
Authors:  Yan, Keyue;  Fong, Simon;  Li, Tengyue;  Song, Qun
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:2.5/2.7 | Submit date：2024/08/05
Machine Learning  Multimodal Data  Renal Cell Carcinoma  Survival Prediction  
Prediction analysis of TBI 24-h survival outcome based on machine learning Journal article
Yang, Yang, Zhou, Liulei, Luo, Jinhua, Xue, Jianhua, Liu, Jiajia, Zhang, Jiajia, Wang, Ziheng, Gong, Peipei, Chen, Tianxi. Prediction analysis of TBI 24-h survival outcome based on machine learning[J]. Heliyon, 2024, 10(9), e30198.
Authors:  Yang, Yang;  Zhou, Liulei;  Luo, Jinhua;  Xue, Jianhua;  Liu, Jiajia; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:3.4/3.9 | Submit date：2024/05/16
Dnn  Knn  Lr  Machine Learning  Rf  Survival  Trauma  
Optimal Size Threshold for MRI-Detected Retropharyngeal Lymph Nodes to Predict Outcomes in Nasopharyngeal Carcinoma: A Two-Center Study Journal article
Zhu, Yuliang, Luo, Chao, Zhou, Shumin, Li, Haojiang, Liu, Lizhi, Kou, Kit Ian, Lei, Feng, Zhang, Guoyi, Cao, Di, Liang, Zhiying. Optimal Size Threshold for MRI-Detected Retropharyngeal Lymph Nodes to Predict Outcomes in Nasopharyngeal Carcinoma: A Two-Center Study[J]. American Journal of Roentgenology, 2024, 222(1), e2329984.
Authors:  Zhu, Yuliang;  Luo, Chao;  Zhou, Shumin;  Li, Haojiang;  Liu, Lizhi; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:4.7/4.1 | Submit date：2024/02/22
Minimal Axial Diameter  Nasopharyngeal Carcinoma  Prognosis  Progression-free Survival  Retropharyngeal Lymph Node  
Coculture of cancer cells with platelets increases their survival and metastasis by activating the TGFβ/Smad/PAI-1 and PI3K/AKT pathways Journal article
Tong, Haibo, Li, Koukou, Zhou, Muya, Wu, Ranfei, Yang, Hongmei, Peng, Zheng, Zhao, Qi, Luo, Kathy Qian. Coculture of cancer cells with platelets increases their survival and metastasis by activating the TGFβ/Smad/PAI-1 and PI3K/AKT pathways[J]. International Journal of Biological Sciences, 2023, 19(13), 4259-4277.
Authors:  Tong, Haibo;  Li, Koukou;  Zhou, Muya;  Wu, Ranfei;  Yang, Hongmei; et al.
Favorite | TC[WOS]:5 TC[Scopus]:7  IF:8.2/8.3 | Submit date：2023/08/23
Cancer Cells  Platelets  Survival  Metastasis  Tgfβ  Pai-1  
Kill Stories: A Critical Narrative in the Zhuangzi. Journal article
Hans-Georg Moeller. Kill Stories: A Critical Narrative in the Zhuangzi.[J]. Dao: A Journal of Comparative Philosophy, 2023, 22(3), 397 - 412.
Authors:  Hans-Georg Moeller
Adobe PDF | Favorite | TC[WOS]:0 TC[Scopus]:0  IF:0.5/0.5 | Submit date：2023/08/08
Zhuangzi 莊子  Daoism  Ritual  Kill Stories  Confucianism  Survival Stories  
Patient-Derived Tumor Organoids Can Predict the Progression-Free Survival of Patients with Stage IV Colorectal Cancer after Surgery Journal article
Wang, Ting, Tang, Yuting, Pan, Wenjun, Yan, Botao, Hao, Yifan, Zeng, Yunli, Chen, Zexin, Lan, Jianqiang, Zhao, Shuhan, Deng, Chuxia, Zheng, Hang, Yan, Jun. Patient-Derived Tumor Organoids Can Predict the Progression-Free Survival of Patients with Stage IV Colorectal Cancer after Surgery[J]. Diseases of the Colon and Rectum, 2023, 66(5), 733-743.
Authors:  Wang, Ting;  Tang, Yuting;  Pan, Wenjun;  Yan, Botao;  Hao, Yifan; et al.
Favorite | TC[WOS]:10 TC[Scopus]:10  IF:3.2/4.0 | Submit date：2023/06/05
Drug Tests  Patient-derived Tumor Organoid  Predictive Model  Prognostic Value  Progression-free Survival  Stage Iv Colorectal Cancer  
Deep-learning-based survival prediction of patients with cutaneous malignant melanoma Journal article
Yu, Hai, Yang, Wei, Wu, Shi, Xi, Shaohui, Xia, Xichun, Zhao, Qi, Ming, Wai Kit, Wu, Lifang, Hu, Yunfeng, Deng, Liehua, Lyu, Jun. Deep-learning-based survival prediction of patients with cutaneous malignant melanoma[J]. Frontiers in Medicine, 2023, 10, 1165865.
Authors:  Yu, Hai;  Yang, Wei;  Wu, Shi;  Xi, Shaohui;  Xia, Xichun; et al.
Favorite | TC[WOS]:2 TC[Scopus]:3  IF:3.1/3.4 | Submit date：2023/08/03
Deepsurv  Cutaneous Malignant Melanoma  Neural Network  Survival Prediction  Seer  
Clinical Benefit of First-Line Programmed Death-1 Antibody Plus Chemotherapy in Low Programmed Cell Death Ligand 1-Expressing Esophageal Squamous Cell Carcinoma: A Post Hoc Analysis of JUPITER-06 and Meta-Analysis Journal article
Wu, Hao Xiang, Pan, Yi Qian, He, Ye, Wang, Zi Xian, Guan, Wen Long, Chen, Yan Xing, Yao, Yi Chen, Shao, Ning Yi, Xu, Rui Hua, Wang, Feng. Clinical Benefit of First-Line Programmed Death-1 Antibody Plus Chemotherapy in Low Programmed Cell Death Ligand 1-Expressing Esophageal Squamous Cell Carcinoma: A Post Hoc Analysis of JUPITER-06 and Meta-Analysis[J]. Journal of Clinical Oncology, 2023, 41(9), 1735-1746.
Authors:  Wu, Hao Xiang;  Pan, Yi Qian;  He, Ye;  Wang, Zi Xian;  Guan, Wen Long; et al.
Favorite | TC[WOS]:30 TC[Scopus]:32  IF:42.1/37.4 | Submit date：2023/04/03
Pembrolizumab  Placebo  Camrelizumab  Nivolumab  Survival  Efficacy  Therapy  Safety  Chemo  
Deep learning-extracted CT imaging phenotypes predict response to total resection in colorectal cancer Journal article
Pan, Xiang, Cong, He, Wang, Xiaolei, Zhang, Heng, Ge, Yuxi, Hu, Shudong. Deep learning-extracted CT imaging phenotypes predict response to total resection in colorectal cancer[J]. Acta Radiologica, 2023, 64(5), 1783-1791.
Authors:  Pan, Xiang;  Cong, He;  Wang, Xiaolei;  Zhang, Heng;  Ge, Yuxi; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.1/1.4 | Submit date：2023/06/05
Colorectal Cancer  Computed Tomography  Deep Learning  Overall Survival  Self-learning High-throughput Features