📄Predicting the establishment and removal of global trade relations for import and export of petrochemical products

📘Journal: Energy (I.F=8.857)
🗓Publish year: 2023

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📱Channel: @ComplexNetworkAnalysis
#paper #prediction #trade #petrochemical

📄Disease Prediction Using Graph Machine Learning Based on Electronic Health Data: A Review of Approaches and Trends

📘journal: HEALTHCARE-BASEL (I.F=2.8)
🗓Publish year: 2023

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📱Channel: @ComplexNetworkAnalysis
#paper #Disease #Prediction #Graph_Machine_Learning #Electronic #Health #Trends #Review

📄Recent Advances in Network-based Methods for
Disease Gene Prediction

📘journal: Briefings in bioinformatics (I.F= 9.5)
🗓Publish year: 2021

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📱Channel: @ComplexNetworkAnalysis
#paper #Advances #Network_based_Methods #Disease #Gene #Prediction

📄Structure-oriented prediction in complex networks

📘 Journal: Physics Reports (IF=25.6)
🗓Publish year: 2018

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📲Channel: @ComplexNetworkAnalysis
#paper #prediction

📄A Survey on Hyperlink Prediction

🗓Publish year: 2022

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📱Channel: @ComplexNetworkAnalysis
#paper #Hyperlink #prediction #survey

📃 Integrating sentiment analysis with graph neural networks for enhanced stock prediction: A comprehensive survey

📘 Journal: Decision Analytics Journal
🗓 Publish year: 2024

🧑‍💻Authors: Nabanita Das, Bikash Sadhukhan, Rajdeep Chatterjee, Satyajit Chakrabarti
🏢University: University of Engineering & Management, Kolkata-700160, India

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📱Channel: @ComplexNetworkAnalysis
#paper #Integrating #sentiment #GNN #stock #prediction #survey

📃 Drug-drug interactions prediction based on deep learning and knowledge graph: a review

📘 Journal: iScience (I.F=6.107)
🗓 Publish year: 2024

🧑‍💻Authors: Huimin Luo, Weijie Yin, Jianlin Wang, Wenjuan Liang, Junwei Luo, Chaokun Yan
🏢University: Henan University, Kaifeng, China, Henan Polytechnic University, Jiaozuo, China

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#paper #Drug #prediction #Deep_learning #knowledge_graph #review

📃 Graph neural networks for clinical risk prediction based on electronic health records: A survey

📘 Journal: Journal of Biomedical Informatics (I.F=4.5)
🗓 Publish year: 2024

🧑‍💻Authors: Heloísa Oss Boll, Ali Amirahmadi, Mirfarid Musavian Ghazani, Wagner Ourique de Morais, Edison Pignaton de Freitas, Amira Soliman, Farzaneh Etminani, Stefan Byttner, Mariana Recamonde-Mendoza
🏢Universities: Universidade Federal do Rio Grande do Sul, Halmstad University

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#paper #GNN #risk #prediction #electronic #health #survey

📃Comprehensive evaluation of deep and graph learning on drug–drug interactions prediction

📘 Journal: Briefings in Bioinformatics(I.F=13.994)
🗓 Publish year: 2023

🧑‍💻Authors: Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S Yu, Xiangxiang Zeng
🏢Universities: Xiangtan University, Huazhong Agricultural University, Hunan University,

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#paper #drug_drug_interactions #Graph_Learning #deep_learning #prediction

📃 Graph Convolutional Neural Networks for Traffic
Forecasting and Prediction: A Review

🗓 Publish year: 2024
📘Conference: AIP Conference Proceedings

🧑‍💻Authors: Vandana Singh, Sudip Kumar Sahana, Vandana Bhattacharjee
🏢University: Department of Computer Science & Engineering BIT Mesra, Ranchi, India

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📱Channel: @ComplexNetworkAnalysis
#paper #GCN #Traffic_Forecasting #Prediction #Review

📃 A Short Survey on Graph Neural Networks Based Stock Market Prediction Models

🗓 Publish year: 2024
📘 Conference: The Nineteenth International Conference on Internet and Web Applications and Services

🧑‍💻Authors: Lei Zhou, Jian Yu, Samaneh Madanian , Guiling Wang , Sira Yongchareon, Yuqi Zhang
🗺 Country: China , New Zealand

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#paper #Survey #GNN #Stock_Market #Prediction

📃Introducing New Node Prediction in Graph Mining:
Predicting All Links from Isolated Nodes with Graph
Neural Networks

🗓 Publish year: 2024

🧑‍💻Authors: Damiano Zanardinia, Emilio Serrano
🏢Universities: Departamento de Inteligencia Artificial, ETSI Inform´aticos, Universidad Polit´ecnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain

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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Node #prediction #Isolated

📃A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends

🗓 Publish year: 2024
📘Journal: Mechanical Systems and Signal Processing(I.F=7.9)

🧑‍💻Authors: Yucheng Wang, Min Wu, Xiaoli Lia, Lihua Xie and Zhenghua Chen

🏢Universities: Nanyang Technological University, Singapore

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#paper #GNN #prediction #Remaining #Life #future #Survey