Cargando…

Graph Neural Network for representation learning of lung cancer

The emergence of image-based systems to improve diagnostic pathology precision, involving the intent to label sets or bags of instances, greatly hinges on Multiple Instance Learning for Whole Slide Images(WSIs). Contemporary works have shown excellent performance for a neural network in MIL settings...

Descripción completa

Detalles Bibliográficos
Autores principales:	Aftab, Rukhma, Qiang, Yan, Zhao, Juanjuan, Urrehman, Zia, Zhao, Zijuan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601264/ https://www.ncbi.nlm.nih.gov/pubmed/37884929 http://dx.doi.org/10.1186/s12885-023-11516-8

Ejemplares similares

Using graph convolutional neural networks to learn a representation for glycans
por: Burkholz, Rebekka, et al.
Publicado: (2021)

Editorial: Graph representation learning in biological network
por: Roy, Swarup, et al.
Publicado: (2023)

Graph representation learning
por: Hamilton, William L
Publicado: (2020)

Fast protein structure comparison through effective representation learning with contrastive graph neural networks
por: Xia, Chunqiu, et al.
Publicado: (2022)

Syntactically-informed word representations from graph neural network
por: Tran, Thy Thy, et al.
Publicado: (2020)

Materials fatigue prediction using graph neural networks on microstructure representations
por: Thomas, Akhil, et al.
Publicado: (2023)

Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
por: Jiang, Dejun, et al.
Publicado: (2021)

Text-Graph Enhanced Knowledge Graph Representation Learning
por: Hu, Linmei, et al.
Publicado: (2021)

Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions
por: Yan, Zichao, et al.
Publicado: (2020)

Graph representation learning for structural proteomics
por: Fasoulis, Romanos, et al.
Publicado: (2021)

An integrated network representation of multiple cancer-specific data for graph-based machine learning
por: Pu, Limeng, et al.
Publicado: (2022)

Evaluating graph neural networks under graph sampling scenarios
por: Wei, Qiang, et al.
Publicado: (2022)

Author Correction: Materials fatigue prediction using graph neural networks on microstructure representations
por: Thomas, Akhil, et al.
Publicado: (2023)

Multipath Cross Graph Convolution for Knowledge Representation Learning
por: Tian, Luogeng, et al.
Publicado: (2021)

Learning representations of irregular particle-detector geometry with distance-weighted graph networks
por: Qasim, Shah Rukh, et al.
Publicado: (2019)

Learning representations of irregular particle-detector geometry with distance-weighted graph networks
por: Kieseler, Jan
Publicado: (2019)

Learning graph representations of biochemical networks and its application to enzymatic link prediction
por: Jiang, Julie, et al.
Publicado: (2020)

TCM Prescription Generation via Knowledge Source Guidance Network Combined with Herbal Candidate Mechanism
por: Hou, Jiaxin, et al.
Publicado: (2023)

Representational Distance Learning for Deep Neural Networks
por: McClure, Patrick, et al.
Publicado: (2016)

Neural representations of cryo-EM maps and a graph-based interpretation
por: Ranno, Nathan, et al.
Publicado: (2022)

Subgraph Learning for Topological Geolocalization with Graph Neural Networks
por: Zha, Bing, et al.
Publicado: (2023)

Learning Cortical Parcellations Using Graph Neural Networks
por: Eschenburg, Kristian M., et al.
Publicado: (2021)

Detection of autism spectrum disorder using graph representation learning algorithms and deep neural network, based on fMRI signals
por: Yousefian, Ali, et al.
Publicado: (2023)

Multitask Learning with Graph Neural Network for Travel Time Estimation
por: Yang, Ling, et al.
Publicado: (2022)

Weakly supervised label propagation algorithm classifies lung cancer imaging subtypes
por: Ren, Xueting, et al.
Publicado: (2023)

Study on the Prediction Method of Long-term Benign and Malignant Pulmonary Lesions Based on LSTM
por: Liu, Xindong, et al.
Publicado: (2022)

Graph Representation Learning and Its Applications: A Survey
por: Hoang, Van Thuy, et al.
Publicado: (2023)

Neuro-symbolic representation learning on biological knowledge graphs
por: Alshahrani, Mona, et al.
Publicado: (2017)

LUNAR :Drug Screening for Novel Coronavirus Based on Representation Learning Graph Convolutional Network
Publicado: (2021)

Efficient graph representations
por: Spinrad, Jeremy P
Publicado: (2003)

Network structure influences the strength of learned neural representations
por: Kahn, Ari E., et al.
Publicado: (2023)

Compressed graph representation for scalable molecular graph generation
por: Kwon, Youngchun, et al.
Publicado: (2020)

Representation learning of genomic sequence motifs with convolutional neural networks
por: Koo, Peter K., et al.
Publicado: (2019)

MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning
por: Zhao, Bo-Wei, et al.
Publicado: (2021)

Self-supervised graph neural network with pre-training generative learning for recommendation systems
por: Min, Xin, et al.
Publicado: (2022)

Graph Neural Network-Guided Contrastive Learning for Sequential Recommendation
por: Yang, Xing-Yao, et al.
Publicado: (2023)

Generalizable Machine Learning in Neuroscience Using Graph Neural Networks
por: Wang, Paul Y., et al.
Publicado: (2021)

A Graph Neural Network Based Decentralized Learning Scheme
por: Gao, Huiguo, et al.
Publicado: (2022)

Introduction to graph neural networks
por: Liu, Zhiyuan, et al.
Publicado: (2020)

Predicting Microbe-Disease Association by Learning Graph Representations and Rule-Based Inference on the Heterogeneous Network
por: Lei, Xiujuan, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_9du4esl07hg6ocervtgiv2paho