FHGNet: A Feature-Centric Hierarchical Network with Graph Attention Layer for Supraventricular Tachycardia Classification [0.03%]
基于图注意力层的以特征为中心的分层网络 FHGNet 在室上性心动过速分类中的应用
Xiaolin Ju,Tao Liu,Bowen Luo et al.
Xiaolin Ju et al.
Automated electrocardiogram (ECG) classification plays a critical role in arrhythmia diagnosis. However, current deep learning-based methodologies frequently fail to account for physiological rhythms and clinical diagnostic reasoning, there...
IIC-DTI: A Contrastive Learning Enhanced Inter-Intra Molecular Fusing Framework for Drug-Target Interaction Prediction [0.03%]
基于对比学习的药物靶点相互作用预测的Inter-Intra分子融合框架(IIC-DTI)
Fei Wang,Dacheng Ruan,Yang Zhang et al.
Fei Wang et al.
Purpose: Predicting drug-target interactions (DTIs) is a practical demand in drug development and drug repositioning. Therefore, developing accurate and efficient DTI prediction methods has significant application value. ...
GATRSyn: Advancing Anticancer Drug Synergy Prediction Through Graph Attention Networks and Transformer-based Feature Re-embedding [0.03%]
基于图注意力网络和Transformer特征重新嵌入的抗肿瘤药物协同作用预测方法
Sile Li,Ziyu Li,Chenyang Dong et al.
Sile Li et al.
Multi-Modal Fusion with Supervised Contrastive Learning Model for Early Alzheimer's Disease Diagnosis and Multi-Modal Biomarker Identification [0.03%]
基于监督对比学习模型的多模态融合在阿尔茨海默病早期诊断和生物标志物识别中的应用研究
Xiaofeng Xie,Peng Xue,Yihao Guo et al.
Xiaofeng Xie et al.
Early and accurate diagnosis of mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease (AD), is critical for timely intervention and management. Nevertheless, effectively integrating heterogeneous multi-modal data for AD ...
HRD-Informed Digital Histology Model for Predicting Platinum Chemo-Response and Prognosis in High-Grade Serous Ovarian Cancer [0.03%]
基于HRD的数字病理预测模型在铂类药物化疗疗效及预后中的应用研究（英文）
Zijian Yang,Liujin Zhang,Luyuan Li et al.
Zijian Yang et al.
Homologous recombination deficiency (HRD) is a critical biomarker in high-grade serous ovarian cancer for the clinical benefit from platinum-based chemotherapy and poly polymerase inhibitors, but molecular testing is costly, time-consuming,...
ESM-PsyPred: Leveraging Protein Language Models for Accurate Prediction of Psychrophilic Proteins [0.03%]
基于蛋白质语言模型的 psychrophilic 蛋白预测方法 ESM-PsyPred
Chong Peng,Yarui Bian,Chengwu Yuan et al.
Chong Peng et al.
Psychrophilic proteins, which maintain high activity and stability in low-temperature environments, hold significant potential for industrial and ecological research. However, existing predictive tools predominantly focus on thermophilic pr...
Inferring Phenotypes of Single Cells Based on the Expression Profiles of Phenotype-Associated Marker Genes in Bulks and Single Cells [0.03%]
基于批量和单细胞中与表型相关标记基因的表达谱推断单细胞表型特征
Yin He,Rongzhuo Long,Xiaosheng Wang
Yin He
Single-cell transcriptomes are not sufficient in describing cell phenotypes. Here we propose an algorithm for single cells' phenotype prediction (ScPP) based on the expression profiles of phenotype-associated marker genes in bulks and singl...
Interpretable Multimodal Molecular Language Model for Drug-Target Interaction Prediction [0.03%]
一种用于药物靶点相互作用预测的解释性多模态分子语言模型
Hui Yu,Qingyong Wang,Xiaobo Zhou et al.
Hui Yu et al.
Generative Adversarial Networks Based on Fine-Grained Image Recognition for the Progression Prediction of Progressive Mild Cognitive Impairment [0.03%]
基于细粒度图像识别的生成对抗网络在进展性轻度认知障碍纵向预测中的应用研究
Changsong Shen,Fangxiang Wu,Bo Liao et al.
Changsong Shen et al.
Progressive mild cognitive impairment (pMCI) often develops into Alzheimer's disease (AD), whereas stable mild cognitive impairment (sMCI) remains cognitively unchanged. Therefore, early identification of pMCI based on multimodal neuroimagi...