1. 赫捷 中国 中国医学科学院 中国科学院院士 Knowledge mapping visualization of the pulmonary ground-glass opacity published in the web of scienc..
2. Hiroshi,Okamoto 日本 Tohoku University Multimodal deep-learning model using pre-treatment endoscopic images and clinical information to pre..
3. Unno, Michiaki 日本 Tohoku University Multimodal deep-learning model using pre-treatment endoscopic images and clinical information to pre..
4. Yasushi,Yatabe 日本 Aichi Cancer Center Radiologists Versus AI-Based Software: Predicting Lymph Node Metastasis and Prognosis in Lung Adenoc..
5. Marcello,Tiseo 意大利 University of Hospital PARMA Longitudinal Changes of CT-radiomic and Systemic Inflammatory Features Predict Survival in Advanced ..
6. 郑传胜 中国 华中科技大学 教授、主任医师、博士研究生导师 From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precisi..
7. 邵志敏 中国 复旦大学上海医学院 Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-bi..
8. 田捷 中国 北京航空航天大学 教授 Deep learning model based on primary tumor to predict lymph node status in clinical stage IA lung ad..
9. 王健伟 中国 中国医学科学院 教授 Radiological Features of Primary Pulmonary Invasive Mucinous Adenocarcinoma Based on 312 Consecutive..
10. Frederik L,Giesel 德国 Heidelberg University Prognostic potential of integrated morphologic and metabolic parameters of pre-therapeutic [18<..
11. Gerald,Antoch 德国 University of DUSSELDORF Prognostic potential of integrated morphologic and metabolic parameters of pre-therapeutic [18<..
12. Jaffray, David A. 美国 University of Texas MD Anderson Cancer Center Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenom..
13. Ignacio I,Wistuba 美国 University of Texas MD Anderson Cancer Center Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenom..
14. Lee, J. Jack 美国 University of Texas MD Anderson Cancer Center Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenom..
15. John V,Heymach 美国 University of Texas MD Anderson Cancer Center Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenom..
16. Joe Y,Chang 美国 University of Texas MD Anderson Cancer Center Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenom..
17. Genichiro,Ishii 日本 National Cancer Center Hospital East 2021 WHO Classification of Lung Cancer: Molecular Biology Research and Radiologic-Pathologic Correla..
18. 王健伟 中国 中国医学科学院 教授 Radiological and clinical features of large consolidative-type pulmonary invasive mucinous adenocarc..
19. Rodrigo,Dienstmann 西班牙 Autonomous University of Barcelona A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still l..
20. Regina G. H,Beets-Tan 荷兰 Netherlands Cancer Institute A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still l..