Analyzing Clinical Practice Guidelines Using a Decidable Metric Interval-Based Temporal Logic

Sanati, Morteza Yousef; MacCaull, Wendy; Maibaum, Tom

doi:10.1007/978-3-319-06410-9_41

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…The tree model is constructed using the tableau-based algorithm presented in previous studies (2,3). displays a part of the tree model of the HIV/AIDS CPG.…”

Section: Tree Modelmentioning

confidence: 99%

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Satisfiability Checking of Clinical Practice Guidelines Using an Analyzer

Sanati

Asadi

2020

Mod Care J

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A clinical practice guideline consists of the best practices required for managing a particular disease. Designing a consistent guideline is difficult and error-prone; hence, checking the consistency of guidelines is crucial. Due to the complexity of guidelines, a formal language is an appropriate choice for modeling and analyzing a guideline. IMPNL has been introduced as a metric intervalbased temporal logic to model such guidelines. Moreover, a sound and complete tableau-based algorithm has been designed for checking the satisfiability of an IMPNL formula. In this paper, we introduced a clinical practice guideline analyzer suitable for modeling and checking the consistency of a guideline. The analyzer can also determine points, in which inconsistencies occur, and help designers to quickly and easily fix a guideline. Moreover, physicians can use the output of the analyzer (the calendar model) to check whether a patient is coherently treated with a specific guideline.

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“…The tree model is constructed using the tableau-based algorithm presented in previous studies (2,3). displays a part of the tree model of the HIV/AIDS CPG.…”

Section: Tree Modelmentioning

confidence: 99%

“…There are different formalizations and tools with different functionalities [e.g., Absru (2,3), PROforma (2,3), EON (4), GLIF (2, 3), g-HMSC (5), Little-JIL (6)]. While some of these languages are considered as general-purpose process modeling languages, e.g.…”

Section: Introductionmentioning

confidence: 99%