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arXiv Machine Learning By Yuhua Huang, Hsiao-Ying Lu, Kwan-Liu Ma

Visualizing and Interpreting Temporal Care Team Dynamics for Cancer Survival Risk Analysis

Read the original on arXiv Machine Learning →

The paper presents a visual analytics framework that models and interprets time‑varying care team interactions in oncology. It builds dynamic collaboration networks from electronic health record communication data and applies a temporal graph neural network to estimate patient risk over time. The system integrates risk modeling with coordinated visualizations, feature‑level explanations, and what‑if analysis to help analysts explore how changes in team composition relate to risk shifts across treatment stages.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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