[HTML][HTML] A survey of traffic prediction: from spatio-temporal data to intelligent transportation

H Yuan, G Li - Data Science and Engineering, 2021 - Springer
Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

Graph neural architecture search: A survey

BM Oloulade, J Gao, J Chen, T Lyu… - Tsinghua Science and …, 2021 - ieeexplore.ieee.org
In academia and industries, graph neural networks (GNNs) have emerged as a powerful
approach to graph data processing ranging from node classification and link prediction tasks …

Database meets artificial intelligence: A survey

X Zhou, C Chai, G Li, J Sun - IEEE Transactions on Knowledge …, 2020 - ieeexplore.ieee.org
Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …

Improving cancer driver gene identification using multi-task learning on graph convolutional network

W Peng, Q Tang, W Dai, T Chen - Briefings in Bioinformatics, 2022 - academic.oup.com
Cancer is thought to be caused by the accumulation of driver genetic mutations. Therefore,
identifying cancer driver genes plays a crucial role in understanding the molecular …

Predicting drug response based on multi-omics fusion and graph convolution

W Peng, T Chen, W Dai - IEEE Journal of Biomedical and …, 2021 - ieeexplore.ieee.org
Different cancer patients may respond differently to cancer treatment due to the
heterogeneity of cancer. It is an urgent task to develop an efficient computational method to …

A heterogeneous network embedded medicine recommendation system based on LSTM

I Ahmed, M Ahmad, A Chehri, G Jeon - Future Generation Computer …, 2023 - Elsevier
In the healthcare sector, patient data plays a crucial role in medical diagnoses and treatment
plans. However, existing techniques for finding similar patients based on Electronic Health …

Toward digital twin oriented modeling of complex networked systems and their dynamics: A comprehensive survey

J Wen, B Gabrys, K Musial - Ieee Access, 2022 - ieeexplore.ieee.org
This paper aims to provide a comprehensive critical overview on how entities and their
interactions in Complex Networked Systems (CNS) are modelled across disciplines as they …

[HTML][HTML] Identifying critical nodes in temporal networks by network embedding

EY Yu, Y Fu, X Chen, M Xie, DB Chen - Scientific reports, 2020 - nature.com
Critical nodes in temporal networks play more significant role than other nodes on the
structure and function of networks. The research on identifying critical nodes in temporal …

Biomedical data, computational methods and tools for evaluating disease–disease associations

J Xiang, J Zhang, Y Zhao, FX Wu… - Briefings in …, 2022 - academic.oup.com
In recent decades, exploring potential relationships between diseases has been an active
research field. With the rapid accumulation of disease-related biomedical data, a lot of …

PrGeFNE: predicting disease-related genes by fast network embedding

J Xiang, NR Zhang, JS Zhang, XY Lv, M Li - Methods, 2021 - Elsevier
Identifying disease-related genes is of importance for understanding of molecule
mechanisms of diseases, as well as diagnosis and treatment of diseases. Many …