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In this paper, we present a method that integrates Bayesian network and generalized possibilistic model checking to improve the accuracy of initial diagnostics and quantify uncertainties in the rehabilitation process. Bayesian network provides probabilistic decision support using data-driven statistical information from various sources. Computational tree logic, combined with generalized possibility measures, effectively manages the uncertainties associated with patient rehabilitation.

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Medical Procedures Based on Bayesian Network and Possibilistic Model Checking

  • 会议论文

  • 发表日期：

    2025年

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  • Ying Wen,
  • Qing He,
  • Yongming Li

摘要

In this paper, we present a method that integrates Bayesian network and generalized possibilistic model checking to improve the accuracy of initial diagnostics and quantify uncertainties in the rehabilitation process. Bayesian network provides probabilistic decision support using data-driven statistical information from various sources. Computational tree logic, combined with generalized possibility measures, effectively manages the uncertainties associated with patient rehabilitation.