MLMVFE: A Machine Learning Approach Based on Muli-View Features Extraction for Drug-Disease Associations Prediction.- STgcor: A Distribution-based Correlation MeasurementMethod for Spatial Transcriptome Data.- Automatic ICD Coding based on Multi-granularity Feature Fusion.- Effectively Training MRI Reconstruction Network via Sequentially Using Undersampled k-Space Data with Very Low Frequency Gaps.- Fusing Label Relations for Chinese EMR Named Entity Recognition with Machine Reading Comprehension.- Private Epigenetic PaceMaker Detector using Homomorphic Encryption - Extended Abstract.- NIDN: Medical Code Assignment via Note-Code Interaction Denoising Network.- Research on the prediction method of disease classification based on imaging features.- M-US-EMRs: A Multi-Modal Data Fusion Method of Ultrasonic Images and Electronic Medical Records Used for Screening of Coronary Heart Disease.- Transposition Distance Considering Intergenic Regions for Unbalanced Genomes.- An SMT-based Framework for Reasoning about Discrete Biological Models.- ARGLRR: An Adjusted Random Walk Graph Regularization Sparse Low-rank Representation Method for Single-cell RNA-sequencing Data Clustering.- An Efficient and User-friendly Software for PCR Primer Design for Detection of Highly Variable Bacteria.- A Network-Based Voting Method for Identification and Prioritization of Personalized Cancer Driver Genes.- TDCOSR: A multimodality fusion framework for association analysis between genes and ROIs of Alzheimer’s disease.- Policy-based Hypertension Monitoring using Formal Runtime Verification Monitors.- Deep learning-enhanced MHC-II presentation prediction and peptidome deconvolution.- MMLN: Leveraging Domain Knowledge for Multimodal Diagnosis.- Optimal sequence alignment to ED-strings.- Heterogeneous PPI network representation learning for protein complex identification.- A Clonal Evolution Simulator for Planning Somatic Evolution Studies.- Prediction of Drug-disease Relationship on Heterogeneous Networks Based on Graph Convolution.- t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution.- MPCDDI: A Secure Multiparty Computation-based Deep Learning Framework for Drug-drug Interaction Predictions.- A Multimodal Data Fusion-based Deep Learning Approach for Drug-Drug Interaction Prediction.- GNN-Dom: an unsupervised method for protein domain partition via protein contact map.- A Locality-Constrained Linear Coding-Based Ensemble Learning Framework for Predicting Potentially Disease-Associated MiRNAs.- Gaussian-enhanced Representation Model for Extracting Protein-Protein Interactions Affected by Mutations.- Distance Profiles of Optimal RNA Foldings.- 2D Photogrammetry Image of Adolescent Idiopathic Scoliosis Screening Using Deep Learning.- EMRShareChain: A Privacy-Preserving EMR Sharing System Model Based on the Consortium Blockchain.- Simulating Spiking Neural Networks based on SW26010pro.- Entropy Based Clustering of Viral Sequences.- A Tensor Robust Model Based on Enhanced Tensor Nuclear Norm and Low-Rank Constraint for Multi-view Cancer Genomics Data.
Trade Policy 买家须知
- 关于产品:
- ● 正版保障:本网站隶属于中国国际图书贸易集团公司,确保所有图书都是100%正版。
- ● 环保纸张:进口图书大多使用的都是环保轻型张,颜色偏黄,重量比较轻。
- ● 毛边版:即书翻页的地方,故意做成了参差不齐的样子,一般为精装版,更具收藏价值。
关于退换货:
- 由于预订产品的特殊性,采购订单正式发订后,买方不得无故取消全部或部分产品的订购。
- 由于进口图书的特殊性,发生以下情况的,请直接拒收货物,由快递返回:
- ● 外包装破损/发错货/少发货/图书外观破损/图书配件不全(例如:光盘等)
并请在工作日通过电话400-008-1110联系我们。
- 签收后,如发生以下情况,请在签收后的5个工作日内联系客服办理退换货:
- ● 缺页/错页/错印/脱线
关于发货时间:
- 一般情况下:
- ●【现货】 下单后48小时内由北京(库房)发出快递。
- ●【预订】【预售】下单后国外发货,到货时间预计5-8周左右,店铺默认中通快递,如需顺丰快递邮费到付。
- ● 需要开具发票的客户,发货时间可能在上述基础上再延后1-2个工作日(紧急发票需求,请联系010-68433105/3213);
- ● 如遇其他特殊原因,对发货时间有影响的,我们会第一时间在网站公告,敬请留意。
关于到货时间:
- 由于进口图书入境入库后,都是委托第三方快递发货,所以我们只能保证在规定时间内发出,但无法为您保证确切的到货时间。
- ● 主要城市一般2-4天
- ● 偏远地区一般4-7天
关于接听咨询电话的时间:
- 010-68433105/3213正常接听咨询电话的时间为:周一至周五上午8:30~下午5:00,周六、日及法定节假日休息,将无法接听来电,敬请谅解。
- 其它时间您也可以通过邮件联系我们:customer@readgo.cn,工作日会优先处理。
关于快递:
- ● 已付款订单:主要由中通、宅急送负责派送,订单进度查询请拨打010-68433105/3213。
本书暂无推荐
本书暂无推荐