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An efficient reachability query based pruning algorithm in e-health scenario.

Safikureshi Mondal1, Nandini Mukherjee2

  • 1Department of Computer Science and Engineering, Narula Institute of Technology, Kolkata 700109, West Bengal, India.

Journal of Biomedical Informatics
|April 21, 2019
PubMed
Summary

We developed an efficient pruning algorithm for Disease-Symptom graphs in e-healthcare apps. This method decomposes graphs into symptom trees, improving mobile access to diagnostic data.

Keywords:
graph databaseChain CoverPruning algorithmReachability Query

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Area of Science:

  • Graph databases
  • E-healthcare applications
  • Data mining

Background:

  • Disease-Symptom graph databases are crucial for mobile e-healthcare.
  • Complex graph structures and network limitations hinder efficient querying for preliminary diagnoses.
  • Existing solutions like subgraph generation are needed.

Purpose of the Study:

  • To propose an efficient pruning algorithm for Disease-Symptom graphs.
  • To address challenges in mobile access, query complexity, and network constraints.
  • To improve the performance of e-healthcare applications.

Main Methods:

  • Decomposition of the Disease-Symptom graph into symptom trees (ST).
  • Merging symptom trees to construct a pruned subgraph.
  • Analytical and empirical validation of the pruning algorithm's efficiency.

Main Results:

  • The proposed pruning algorithm demonstrates efficiency and effectiveness.
  • Validation performed on Disease-Symptom and other real-world graph databases.
  • Comparison with the modified Chain Cover algorithm (ChainCoverPrune) shows superior performance.

Conclusions:

  • The novel symptom tree decomposition approach offers an efficient solution for pruning Disease-Symptom graphs.
  • This method enhances the usability of mobile-assisted e-healthcare systems by optimizing data access and querying.
  • The algorithm is validated as a practical and effective tool for graph database management in healthcare.