Predicting Metastatic Risk from Primary Cancer Tissue Architecture via Distance-Aware Spatial Modeling

arXiv:2606.28676 · cs.CV, cs.AI · Submitted 2026-06-27 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-06-27

Updated: 2026-08-31

Terminology

Accuracy — 9× in this paper · explained in 1 episode
Multiple Instance Learning — 9× in this paper
AUC — 7× in this paper · explained in 2 episodes
Benchmark — 7× in this paper · explained in 2 episodes
Foundation Model — 6× in this paper · explained in 3 episodes
Clustering — 5× in this paper · explained in 2 episodes
Ablation — 4× in this paper · explained in 1 episode
Interpretability — 3× in this paper · explained in 15 episodes
Multiple Instance Learning (MIL) — 3× in this paper · explained in 2 episodes
Aggregation — 2× in this paper · explained in 1 episode
Aggregation Function — 2× in this paper · explained in 1 episode
Contrastive Learning — 2× in this paper · explained in 5 episodes
Embeddings — 2× in this paper · explained in 2 episodes
Foundation Models — 2× in this paper · explained in 7 episodes
Ablation study — 1× in this paper · explained in 1 episode
Abstraction — 1× in this paper · explained in 1 episode
Area Under Curve — 1× in this paper
Consistency — 1× in this paper · explained in 3 episodes
Core — 1× in this paper · explained in 2 episodes
Euclidean Distance Transform — 1× in this paper
Explainability — 1× in this paper · explained in 3 episodes
Feature Extraction — 1× in this paper · explained in 2 episodes
Generalizability — 1× in this paper · explained in 6 episodes
Multi-Scale Radial Basis Features — 1× in this paper
Point Clouds — 1× in this paper · explained in 2 episodes
Quadratic Weighted Kappa — 1× in this paper
Transformer — 1× in this paper · explained in 2 episodes
Veterans Affairs — 1× in this paper

Sources

Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

Terminology

Sources

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