Papers › A New Graph Node Classification Benchmark: Learning Structure from Histology Cell Graphs
A New Graph Node Classification Benchmark: Learning Structure from Histology Cell Graphs
Claudia Vanea, Jonathan Campbell, Omri Dodi, Liis Salumäe, Karen Meir, Drorith Hochner-Celnikier, Hagit Hochner, Triin Laisk, Linda M. Ernst, Cecilia M. Lindgren, Christoffer Nellåker
We introduce a new benchmark dataset, Placenta, for node classification in an underexplored domain: predicting microanatomical tissue structures from cell graphs in placenta histology whole slide images. This problem is uniquely challenging for graph learning for a few reasons. Cell graphs are large (>1 million nodes per image), node features are varied (64-dimensions of 11 types of cells), class labels are imbalanced (9 classes ranging from 0.21% of the data to 40.0%), and cellular communities cluster into heterogeneously distributed tissues of widely varying sizes (from 11 nodes to 44,671 nodes for a single structure). Here, we release a dataset consisting of two cell graphs from two placenta histology images totalling 2,395,747 nodes, 799,745 of which have ground truth labels. We present inductive benchmark results for 7 scalable models and show how the unique qualities of cell graphs can help drive the development of novel graph neural network architectures.
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Node Classification | Placenta | GraphSAGE | Accuracy (%) | 64.88±0.43 | #1 of 5 | Archive leaderboard | report |
| Node Classification | Placenta | SIGN | Accuracy (%) | 64.77±0.43 | #2 of 5 | Archive leaderboard | report |
| Node Classification | Placenta | ClusterGCN | Accuracy (%) | 64.24±1.21 | #3 of 5 | Archive leaderboard | report |
| Node Classification | Placenta | GraphSAINT | Accuracy (%) | 63.94±0.23 | #4 of 5 | Archive leaderboard | report |
| Node Classification | Placenta | ShaDow | Accuracy (%) | 63.04±0.77 | #5 of 5 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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