Data Mining in Clinical Practices Guidelines

Article ID

CSTSDE24873

Data Mining in Clinical Practices Guidelines

Dr. Prof. Mayura Kinikar
Dr. Prof. Mayura Kinikar
DOI

Abstract

This paper proposes text mining of clinical practices to extract decision-making steps. These steps should be formed in- logical functions capable of branching on different plan set on some deciding variables. The probable action sequence will be notified on the data of patient given to the conditions of clinical guideline and this will also give critical conditions that need immediate attention. In this project medical grammar rules are applied to extract key decision making steps from the clinical guidelines. In the first step lexical analysis is performed to key- words like ‘if this then perform this, all the medical terms will be identified and this extracted rule set will be used to create a XSLT file. The patient data in form of an XML file will be then applied to the XSLT transformations or rule sets to derive final result of action plan specific to that patient.

Data Mining in Clinical Practices Guidelines

This paper proposes text mining of clinical practices to extract decision-making steps. These steps should be formed in- logical functions capable of branching on different plan set on some deciding variables. The probable action sequence will be notified on the data of patient given to the conditions of clinical guideline and this will also give critical conditions that need immediate attention. In this project medical grammar rules are applied to extract key decision making steps from the clinical guidelines. In the first step lexical analysis is performed to key- words like ‘if this then perform this, all the medical terms will be identified and this extracted rule set will be used to create a XSLT file. The patient data in form of an XML file will be then applied to the XSLT transformations or rule sets to derive final result of action plan specific to that patient.

Dr. Prof. Mayura Kinikar
Dr. Prof. Mayura Kinikar

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Prof. Mayura Kinikar. 2012. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C12): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Data Mining in Clinical Practices Guidelines

Dr. Prof. Mayura Kinikar
Dr. Prof. Mayura Kinikar

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