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Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors Journal article
Ya-Ting Jan, Pei-Shan Tsai, Wen-Hui Huang, Ling-Ying Chou, Shih-Chieh Huang, Jing-Zhe Wang, Pei-Hsuan Lu, Dao-Chen Lin, Chun-Sheng Yen, Ju-Ping Teng, Greta S. P. Mok, Cheng-Ting Shih, Tung-Hsin Wu. Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors[J]. Insights into Imaging, 2023, 14(1).
Authors:  Ya-Ting Jan;  Pei-Shan Tsai;  Wen-Hui Huang;  Ling-Ying Chou;  Shih-Chieh Huang; et al.
Favorite | TC[WOS]:19 TC[Scopus]:21  IF:4.1/5.9 | Submit date：2023/08/03
Computed Tomography  Deep Learning  Machine Learning  Ovarian Tumor  Radiomics  
Editorial: Community series in novel insights into immunotherapy targeting tumor microenvironment in ovarian cancer: volume I Other
2023-04-11
Authors:  Di,Xiang Jie;  Zhao,Qi;  Wang,Hai Tao;  Wei,Xia Wei;  Liang,Xiao
Favorite | TC[WOS]:1 TC[Scopus]:1 | Submit date：2023/08/03
Exosomes  Immunotherapy  Non-tumor Cells Targeting  Ovarian Cancer  Tumor Immune Microenvironment  
Diagnostic extended usefulness of RMI: comparison of four risk of malignancy index in preoperative differentiation of borderline ovarian tumors and benign ovarian tumors Journal article
Shuang Zhang, Shan Yu, Wenying Hou, Xiaoying Li, Chunping Ning, Yingnan Wu, Feng Zhang, Yu Fei Jiao, Leo Tsz On Lee, Litao Sun. Diagnostic extended usefulness of RMI: comparison of four risk of malignancy index in preoperative differentiation of borderline ovarian tumors and benign ovarian tumors[J]. JOURNAL OF OVARIAN RESEARCH, 2019, 12(1).
Authors:  Shuang Zhang;  Shan Yu;  Wenying Hou;  Xiaoying Li;  Chunping Ning; et al.
Favorite | TC[WOS]:14 TC[Scopus]:16  IF:3.8/4.2 | Submit date：2020/05/15
Borderline Ovarian Tumor  Preoperative Evaluation  Risk Of Malignancy Index  Differential Diagnosis  Benign Ovarian Tumor