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Combining task execution and background knowledge for the verification of medical guidelines

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Title: Combining task execution and background knowledge for the verification of medical guidelines
Authors: Hommersom, Arjen1 arjenh@cs.ru.nl, Groot, Perry1, Lucas, Peter1, Balser, Michael2, Schmitt, Jonathan2
Source: Knowledge-Based Systems. Mar2007, Vol. 20 Issue 2, p113-119. 7p.
Subjects: Software verification, Electronic data processing, Machine theory, Type 2 diabetes, Diabetes, Expert systems, Parallel computers, Parallel processing, Medical care
Abstract: The use of a medical guideline can be seen as the execution of computational tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a "network of tasks", i.e., as a number of steps that have a specific function or goal. To investigate the quality of such guidelines we propose a formalization of criteria for good practice medicine a guideline should comply to. We use this theory in conjunction with medical background knowledge to verify the quality of a guideline dealing with diabetes mellitus type 2 using the interactive theorem prover KIV. Verification using task execution and background knowledge is a novel approach to quality checking of medical guidelines. [Copyright &y& Elsevier]
Copyright of Knowledge-Based Systems is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 24192700
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Data: Combining task execution and background knowledge for the verification of medical guidelines
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  Data: <searchLink fieldCode="JN" term="%22Knowledge-Based+Systems%22">Knowledge-Based Systems</searchLink>. Mar2007, Vol. 20 Issue 2, p113-119. 7p.
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  Data: <searchLink fieldCode="DE" term="%22Software+verification%22">Software verification</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+theory%22">Machine theory</searchLink><br /><searchLink fieldCode="DE" term="%22Type+2+diabetes%22">Type 2 diabetes</searchLink><br /><searchLink fieldCode="DE" term="%22Diabetes%22">Diabetes</searchLink><br /><searchLink fieldCode="DE" term="%22Expert+systems%22">Expert systems</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+computers%22">Parallel computers</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+processing%22">Parallel processing</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+care%22">Medical care</searchLink>
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  Data: The use of a medical guideline can be seen as the execution of computational tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a "network of tasks", i.e., as a number of steps that have a specific function or goal. To investigate the quality of such guidelines we propose a formalization of criteria for good practice medicine a guideline should comply to. We use this theory in conjunction with medical background knowledge to verify the quality of a guideline dealing with diabetes mellitus type 2 using the interactive theorem prover KIV. Verification using task execution and background knowledge is a novel approach to quality checking of medical guidelines. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Knowledge-Based Systems is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=24192700
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        Value: 10.1016/j.knosys.2006.11.005
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      – Code: eng
        Text: English
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        Type: general
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      – SubjectFull: Machine theory
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      – SubjectFull: Medical care
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      – TitleFull: Combining task execution and background knowledge for the verification of medical guidelines
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              Text: Mar2007
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              Y: 2007
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