清醒 发表于 2025-3-28 18:34:28
Saeid Asgari Taghanaki,Arkadeep Das,Ghassan Hamarnehing & analysis, liquid biopsies, and more.Relates cancer gen.This popular textbook, now in its third edition, provides a theoretical framework for understanding why cancers arise, how they develop and how they can be treated..Particular attention is devoted to the origins of cancer and the applicatiNeolithic 发表于 2025-3-28 21:19:30
http://reply.papertrans.cn/95/9418/941734/941734_42.png啮齿动物 发表于 2025-3-28 23:18:10
http://reply.papertrans.cn/95/9418/941734/941734_43.png弯弯曲曲 发表于 2025-3-29 04:49:45
Sérgio Pereira,Raphael Meier,Victor Alves,Mauricio Reyes,Carlos A. Silvao treat patients with cancer, which includes Surgery, Radiation therapy, Chemotherapy, Targeted therapy and Immunotherapy. The efficiency of all these treatments is limited by the capacity of cancer cells to escape therapy. This book explains the mechanisms of anti-cancer drug resistance and strateg未开化 发表于 2025-3-29 10:52:17
http://reply.papertrans.cn/95/9418/941734/941734_45.pngEWER 发表于 2025-3-29 12:06:46
http://reply.papertrans.cn/95/9418/941734/941734_46.pngCantankerous 发表于 2025-3-29 17:30:27
http://reply.papertrans.cn/95/9418/941734/941734_47.pngAFFIX 发表于 2025-3-29 23:14:34
http://reply.papertrans.cn/95/9418/941734/941734_48.pngGET 发表于 2025-3-30 01:47:23
Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Datadology to measure the impact of batch effects in classification studies and propose a technique for solving batch effects under the assumption that they are caused by a linear transformation. We empirically show that this approach consistently improve the performance of classifiers in multi-site sce按时间顺序 发表于 2025-3-30 07:58:07
To Learn or Not to Learn Features for Deformable Registration?ld for low level features. This shows that when handcrafted features are designed based on good insights into the problem at hand, they perform better or are comparable to features learnt using deep learning framework.