Text Extraction Engine to Upgrade Clinical Decision Support System
Journal Title: Invention Journal of Research Technology in Engineering & Management - Year 2018, Vol 2, Issue 3
Abstract
New generation technological improvements lead patients to search their symptoms and corresponding diagnosis on online resources. In this study, it is aimed to develop a machine learning model to suit in different availability of users. Most of the current systems allow people to choose related symptom in web interfaces. In addition to these applications it is aimed to implement a new technique which extracts the text-based symptoms and its related parameters such as, severity, duration, location, cause, accompanied by any other indicators. This study is applicable for patient`s everyday language statements besides medical expression of symptoms for corresponding symptoms which is also supporting initial clinical decision system. Extracted terms are analyzed for matching diagnosis where an accuracy of 90% has been accomplished.
Authors and Affiliations
Merve Kevser Gökgöl
Keywords
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