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Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions

18 June 2023
Fang Li
Yi Nian
Zenan Sun
Cui Tao
    LM&MAOODAI4TSAI4CE
ArXiv (abs)PDFHTML
Abstract

Graph representation learning (GRL) has emerged as a pivotal field that has contributed significantly to breakthroughs in various fields, including biomedicine. The objective of this survey is to review the latest advancements in GRL methods and their applications in the biomedical field. We also highlight key challenges currently faced by GRL and outline potential directions for future research.

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