A survey on hypergraph neural networks: An in-depth and step-by-step guide

S Kim, SY Lee, Y Gao, A Antelmi, M Polato… - Proceedings of the 30th …, 2024 - dl.acm.org
Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and
applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda …

Graph Artificial Intelligence in Medicine

R Johnson, MM Li, A Noori, O Queen… - Annual Review of …, 2024 - annualreviews.org
In clinical artificial intelligence (AI), graph representation learning, mainly through graph
neural networks and graph transformer architectures, stands out for its capability to capture …

Graph ai in medicine

R Johnson, MM Li, A Noori, O Queen… - ar** based on EHR Data
Z Zhang, H Cui, R Xu, Y **e, JC Ho… - Proceedings of the 30th …, 2024 - dl.acm.org
The growing availability of well-organized Electronic Health Records (EHR) data has
enabled the development of various machine learning models towards disease risk …

Development of Interpretable Machine Learning Models for COVID-19 Drug Target Docking Scores Prediction

W Shi, M Murakoso, X Guo… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
With the extensive time and financial requirements incumbent on drug discovery,
computational approaches, such as protein-ligand docking predictions, are increasingly …

Effective Surrogate Models for Docking Scores Prediction of Candidate Drug Molecules on SARS-CoV-2 Protein Targets

W Shi, M Murakoso, X Guo, L **ong… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
Emerging infectious diseases, such as coronavirus disease 2019 (COVID-19), pose a major
threat to public health and present a critical challenge for drug discovery. Due to the cost …