Titlebook: Bioinformatics Research and Applications; 20th International S Wei Peng,Zhipeng Cai,Pavel Skums Conference proceedings 2024 The Editor(s) (

FLAW

书目名称Bioinformatics Research and Applications影响因子(影响力)




书目名称Bioinformatics Research and Applications影响因子(影响力)学科排名




书目名称Bioinformatics Research and Applications网络公开度




书目名称Bioinformatics Research and Applications网络公开度学科排名




书目名称Bioinformatics Research and Applications被引频次




书目名称Bioinformatics Research and Applications被引频次学科排名




书目名称Bioinformatics Research and Applications年度引用




书目名称Bioinformatics Research and Applications年度引用学科排名




书目名称Bioinformatics Research and Applications读者反馈




书目名称Bioinformatics Research and Applications读者反馈学科排名

险代理人

骨

清楚说话

改进

Metallurgical Process Engineeringact and fuse key features. We validated the performance of the model on the publicly available dataset TCGA-COAD, and the experimental results demonstrated the superior ability of CovAttnNet in predicting the status of colon cancer MSI status. This study provides a new method for deep learning in marker prediction research.

Oversee

,Patch-Based Coupled Attention Network to Predict MSI Status in Colon Cancer,act and fuse key features. We validated the performance of the model on the publicly available dataset TCGA-COAD, and the experimental results demonstrated the superior ability of CovAttnNet in predicting the status of colon cancer MSI status. This study provides a new method for deep learning in marker prediction research.

debacle

Die Theorie des Metallspritzens,ation module (LRM) for global and local features extraction, respectively, and then fuses global and local features for final classification. The experimental results show the effectiveness and potential of the proposed HM-HER2 model in the field of H &E-stained whole slide images (WSIs) classification of breast cancer.

Indent

Metallurgical Design and Industryised deep neural network is trained with cross-entropy loss and a contrastive regularization term to predict the types of the remaining cells. During this process, the labels of some cells are corrected from one cell type to another, a phenomenon that can also be elucidated from various biological perspectives.

Irrepressible

https://doi.org/10.1007/978-3-642-13956-7ients and healthy controls. Our findings demonstrate higher classification accuracy using time-varying features compared to static brain network topology features. This study enhances our understanding of the dynamic brain network mechanisms in ASD and suggests reliable methods for early diagnosis.

Indurate

,A Hybrid Feature Fusion Network for Predicting HER2 Status on H &E-Stained Histopathology Images,ation module (LRM) for global and local features extraction, respectively, and then fuses global and local features for final classification. The experimental results show the effectiveness and potential of the proposed HM-HER2 model in the field of H &E-stained whole slide images (WSIs) classification of breast cancer.