Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 56 of its 110 references that are in the map. First posted on arXiv 18 Jun 2023.
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56 of 110 references.
References · 56
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38 more
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