Intelligent Computing Theories and Application

17th International Conference, ICIC 2021, Shenzhen, China, August 12–15, 2021, Proceedings, Part III

AvDe-Shuang Huang,Kang-Hyun Jo

Häftad, Engelska, 2021

Del 12838 i serien Lecture Notes in Computer Science

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Beskrivning

This two-volume set of LNCS 12836 and LNCS 12837 constitutes - in conjunction with the volume LNAI 12838 - the refereed proceedings of the 17th International Conference on Intelligent Computing, ICIC 2021, held in Shenzhen, China in August 2021.

Produktinformation

Utgivningsdatum:2021-08-10
Mått:155 x 235 x 37 mm
Vikt:1 031 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:669
Förlag:Springer Nature Switzerland AG
ISBN:9783030845315

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Tillämpad datateknik inom Data och IT

Innehållsförteckning

Artificial Intelligence in Real World Applications.- Task-oriented Snapshot Network Construction of Stock Market.- Analysis of elimination algorithm based on curve self-intersection.- Towards AI-based Reaction and Mitigation for e-commerce - the ENSURESEC Engine.- Arabic Light Stemmer Based on ISRI Stemmer.- Biomedical Informatics Theory and Methods.- Predicting miRNA-disease associations via a new MeSH headings representation of diseases and eXtreme Gradient Boosting.- Social Media Adverse Drug Reaction Detection based on Bi-LSTM with Multi-head Attention Mechanism.- HOMC: a hierarchical clustering algorithm based on optimal low rank matrix completion for single cell analysis.- mzMD: A new storage and retrieval system for mass spectrometry data.- Drug-target Interaction Prediction via Multiple Output Graph Convolutional Networks.- Inversion of k-nearest neighbours algorithm for extracting SNPs discriminating human populations.- ComPAT: a comprehensive pathway analysistools.- Incorporating Knowledge Base for Deep Classification of Fetal Heart Rate.- Review of methods for data collection experiments with people with dementia and the impact of COVID-19.- KGRN: Knowledge Graph Relational Path Network for Target Prediction of TCM Prescriptions.- Challenges in data capturing and collection for physiological detection of dementia-related difficulties and proposed solutions.- Exploring multi-scale temporal and spectral CSP feature for multi-class motion imagination task classification.- Gingivitis detection by Wavelet Energy Entropy and Linear Regression Classifier.- Decomposition-and-Fusion Network for HE-stained Pathological Image Classification.- Complex Diseases Informatics.- A novel approach for predicting microbe-disease associations by structural perturbation method.- A reinforcement learning-Based model for Human microRNA-disease association prediction.- Delineating QSAR descriptors to explore the inherent properties of naturally occurringpolyphenols, responsible for alpha-synuclein amyloid disaggregation scheming towards effective therapeutics against Parkinson’s disorder.- Study on the mechanism of Cistanche in the treatment of colorectal cancer based on network pharmacology.- A Novel Hybrid Machine Learning Approach Using Deep Learning for the Prediction of Alzheimer Disease Using Genome Data.- Prediction of Heart Disease Probability Based on Various Body Function.- Classification of Pulmonary Diseases from X-ray Images Using a Convolutional Neural Network.- Predicting lncRNA-disease associations based on tensor decomposition method.- AI in Skin Cancer Detection.- MiRNA-Disease Associations Prediction based on Neural Tensor Decomposition.- Gene Regulation Modeling and Analysis.- SHDC: A Method of Similarity Measurement Using Heat Kernel based on Denoising for Clustering scRNA-seq Data.- Research on RNA Secondary Structure Prediction Based on MLP.- Inference of Gene Regulatory Network from Time Series Expression Data by Combining Local Geometric Similarity and Multivariate Regression.- Deep Convolution Recurrent Neural Network for Predicting RNA-Protein Binding Preference in mRNA UTR region.- Joint Association Analysis Method to Predict Genes Related to Liver Cancer.- A Hybrid Deep Neural Network for the Prediction of in-vivo Protein-DNA Binding by combining multiple-instance learning.- Using deep learning to predict transcription factor binding sites combining raw DNA sequence, evolutionary information and epigenomic data.- An abnormal gene detection method based on Selene.- A method for constructing an integrative network of competing endogenous RNAs.- Intelligent Computing in Computational Biology.- Detection of Drug-drug Interactions through Knowledge Graph Integrating Multi-attention with Capsule Network.- SCEC: A Novel Single-Cell Classification Method Based on Cell-Pair Ensemble Learning.- ICNNMDA: An Improved Convolutional Neural Network for Predicting miRNA-disease Associations.- DNA-GCN: Graph convolutional networks for predicting DNA-protein binding.- Weighted Nonnegative Matrix Factorization based on Multi-Source Fusion Information for Predicting CircRNA-Disease Associations.- ScSSC: semi-supervised single cell clustering based on 2D embedding.- SNEMO: Spectral Clustering Based on the Neighborhood for Multi-omics Data.- Covid-19 detection by Wavelet Entropy and Jaya.- An ensemble learning algorithm for predicting HIV-1 protease cleavage sites.- RWRNCP: Random Walking with Restart based Network Consistency Projection for Predicting miRNA-disease Association.- MELPMDA: A New Method Based on Matrix Enhancement and Label Propagation for Predicting miRNA-disease Association.- Prognostic prediction for non-small-cell lung cancer based on deep neural network and multimodal data.- Drug-Target Interactions Prediction with Feature Extraction Strategy Based on Graph Neural Network.- CNNEMS: Using Convolutional Neural Networks to Predict Drug-Target Interactions by Combining Protein Evolution and Molecular Structures Information.- A multi-graph deep learning model for predicting drug-disease associations.- Predicting Drug-disease Associations Based on Network Consistency Projection.- An efficient computational method to predict drug-target interactions utilizing matrix completion and linear optimization method.- Protein Structure and Function Prediction.- Protein-Protein Interaction Prediction by Integrating Sequence Information and Heterogeneous Network Representation.- DNA-Binding Protein Prediction Based on Deep Learning Feature Fusion.- Membrane Protein identification via multiple kernel fuzzy SVM.- Golgi Protein Prediction with Deep Forest.- Prediction of protein-protein interaction based on deep learning feature representation and random forest.-