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. 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..
3. Elizaveta,Kon 意大利 Humanitas University Mission (im)possible: meniscal preservation and cartilage regeneration
4. 韩新巍 中国 郑州大学 Radiogenomics: a key component of precision cancer medicine
5. Adnan I,Qureshi 美国 University of Missouri Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation an..
6. Werring, David John 英国 University College London Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation an..
7. Kevin N,Sheth 美国 Yale University Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation an..
8. James,Larkin 英国 Royal Marsden NHS Foundation Trust Interpretability of radiomics models is improved when using feature group selection strategies for p..
9. Dow-Mu,Koh 英国 Royal Marsden NHS Foundation Trust Interpretability of radiomics models is improved when using feature group selection strategies for p..
10. David I,Quinn 美国 University of Southern California Radiogenomic associations clear cell renal cell carcinoma: an exploratory study
11. Gill, Inderbir S. 美国 University of Southern California Radiogenomic associations clear cell renal cell carcinoma: an exploratory study
12. 李为民 中国 四川大学 Predicting gene mutation status via artificial intelligence technologies based on multimodal integra..
13. Riccardo,Autorino 美国 Glickman Urol & Kidney Institute Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects
14. Evis,Sala 英国 University of Cambridge Introduction to radiomics for a clinical audience
15. Riccardo,Autorino 美国 Glickman Urol & Kidney Institute Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature re..
16. 刘新峰 中国 东部战区总医院 A non-contrast computed tomography-based radiomics nomogram for the prediction of hematoma expansion..
17. Young Kwang,Chae 美国 Northwestern University Artificial Intelligence-based Radiomics in the Era of Immuno-Oncology
18. 刘鸣 中国 四川大学 Radiomics-based prediction of hemorrhage expansion among patients with thrombolysis/thrombectomy rel..
19. Matthew S,Davenport 美国 University of Michigan Assessment of Renal Cell Carcinoma by Texture Analysis in Clinical Practice: A Six-Site, Six-Platfor..
20. Nicola,Schieda 加拿大 University of Ottawa Assessment of Renal Cell Carcinoma by Texture Analysis in Clinical Practice: A Six-Site, Six-Platfor..