1. 丛斌 中国 河北医科大学 中国工程院院士 Multi-omits analysis of pathological changes in the amygdala of rats subjected to chronic restraint ..
2. 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..
3. William T,Couldwell 美国 University of Utah The clinical potential of radiomics to predict hematoma expansion in spontaneous intracerebral hemor..
4. 谢鹏 中国 重庆医科大学 主任医师 Quantitative imaging for predicting hematoma expansion in intracerebral hemorrhage: A multimodel com..
5. Adnan I,Qureshi 美国 University of Missouri Radiomic Features of Acute Cerebral Hemorrhage on Non-Contrast CT Associated with Patient Survival
6. Kevin N,Sheth 美国 Yale University Radiomic Features of Acute Cerebral Hemorrhage on Non-Contrast CT Associated with Patient Survival
7. Aviv, Richard I. 加拿大 University of Ottawa Clinical Features, Non-Contrast CT Radiomic and Radiological Signs in Models for the Prediction of H..
8. Elizaveta,Kon 意大利 Humanitas University Mission (im)possible: meniscal preservation and cartilage regeneration
9. 韩新巍 中国 郑州大学 二级教授、主任医师、医学博士、博士生导师 Radiogenomics: a key component of precision cancer medicine
10. Adnan I,Qureshi 美国 University of Missouri Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation an..
11. Werring, David John 英国 University College London Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation an..
12. Kevin N,Sheth 美国 Yale University Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation an..
13. James,Larkin 英国 Royal Marsden NHS Foundation Trust Interpretability of radiomics models is improved when using feature group selection strategies for p..
14. Dow-Mu,Koh 英国 Royal Marsden NHS Foundation Trust Interpretability of radiomics models is improved when using feature group selection strategies for p..
15. David I,Quinn 美国 University of Southern California Radiogenomic associations clear cell renal cell carcinoma: an exploratory study
16. Gill, Inderbir S. 美国 University of Southern California Radiogenomic associations clear cell renal cell carcinoma: an exploratory study
17. 李为民 中国 四川大学 Predicting gene mutation status via artificial intelligence technologies based on multimodal integra..
18. Riccardo,Autorino 美国 Glickman Urol & Kidney Institute Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects
19. Evis,Sala 英国 University of Cambridge Introduction to radiomics for a clinical audience
20. Riccardo,Autorino 美国 Glickman Urol & Kidney Institute Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature re..