Predicting Emergency Medical Service Demand With Bipartite Graph Convolutional Networks

Predicting Emergency Medical Service Demand With Bipartite Graph Convolutional Networks

Emergency medical service (EMS) plays an essential role in increasing survival rates as it provides first aid to victims of life-threatening emergencies. However, unbalanced EMS supply-demand distribution in the metropolis may cause a shortage of accessible EMS resources and delay the first aid trea...

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Bibliographic Details
Main Authors: Ruidong Jin, Tianqi Xia, Xin Liu, Tsuyoshi Murata, Kyoung-Sook Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Bipartite graph embedding
binary label classification
demand modeling
emergency medical service
emergency event prediction
graph convolutional network
Online Access:https://ieeexplore.ieee.org/document/9319153/

Internet

https://ieeexplore.ieee.org/document/9319153/

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