1. 于起峰 中国 国防科技大学 中国科学院院士 Radiomics and artificial intelligence in breast imaging: a survey
2. 郎景和 中国 中国医学科学院 中国工程院院士 Computed tomography-based radiomic model at node level for the prediction of normal-sized lymph node..
3. Dirk,De Ruysscher 荷兰 Maastricht University Whole lung radiomic features are associated with overall survival in patients with locally advanced ..
4. Zhou, Xiaobo 美国 University of Texas Health Science Center at Houston Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features f..
5. 吴一龙 中国 广东省人民医院 教授、主任医师 Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer
6. 张学工 中国 清华大学 教授 Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer
7. Denis,Querleu 意大利 McGill University Radiomics systematic review in cervical cancer: gynecological oncologists' perspective
8. Gabriella,Ferrandina 意大利 University of Cattolica Sacro Cuore Radiomics systematic review in cervical cancer: gynecological oncologists' perspective
9. Giovanni,Scambia 意大利 University of Cattolica Sacro Cuore Radiomics systematic review in cervical cancer: gynecological oncologists' perspective
10. Regina G. H,Beets-Tan 荷兰 Netherlands Cancer Institute Radiomics and artificial intelligence in breast imaging: a survey
11. 田捷 中国 北京航空航天大学 教授 What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence ..
12. Prabhash, Kumar 印度 Tata Memorial Hospital Development and validation of radiomic signature for predicting overall survival in advanced-stage c..
13. Prabhash, Kumar 印度 Tata Memorial Hospital Systematic review and meta-analysis of prediction models used in cervical cancer
14. 李远清 中国 华南理工大学 博士生导师 Prototypical multiple instance learning for predicting lymph node metastasis of breast cancer from w..
15. 田捷 中国 北京航空航天大学 教授 A Novel Deep Learning Framework Based Mask-Guided Attention Mechanism for Distant Metastasis Predict..
16. 李为民 中国 四川大学 A Novel Deep Learning Framework Based Mask-Guided Attention Mechanism for Distant Metastasis Predict..
17. Stief, Christian G 德国 Klinikum der Universität München Radiomics Signature Using Manual Versus Automated Segmentation for Lymph Node Staging of Bladder Can..
18. Ricke, Jens 德国 University of Munich Radiomics Signature Using Manual Versus Automated Segmentation for Lymph Node Staging of Bladder Can..
19. Ciardelli, Gianluca 意大利 Politecnico di Torino Use of Polyesters in Fused Deposition Modeling for Biomedical Applications
20. Barton, Michael B. 澳大利亚 UNSW Medicine Repeatability and reproducibility of magnetic resonance imaging-based radiomic features in rectal ca..