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A knowledge-based system to find over-the-counter medicines for self-medication.

Abstract：

:This study developed a medicine query system based on Semantic Web and open data especially for self-medication users to search over-the-counter (OTC) medicines. Most existing medicine query systems are based on keyword searches. If users are uncertain about the exact search words, these query systems do not offer effective help. Furthermore, most systems provide inadequate explanations of symptoms and ailments for users to use with confidence. To remedy these issues, this study builds a knowledge base to enable inference-based searches and data mashup for integrating information from across the Web. Three components were identified: (1) building an ontology model to describe the relationships between ailments and symptoms; (2) upgrading medicinal product datasets to link them with the ontology model on a semantic level; and (3) developing a data mashup to integrate web resources to help users to find references. Furthermore, the aim was to develop a web-based application that utilizes inference mechanisms to provide users with tools for interactive manipulation. A pilot experiment for skin ailments was implemented to learn the problem-solving skills of the system. Finally, two experts utilized a content validity index to rate a four-dimension 15-item scale. The evaluation results show that experts found the proposed system excellent for content validity.

journal_name

J Biomed Inform

journal_title

Journal of biomedical informatics

authors

Sung HY,Chi YL

doi

10.1016/j.jbi.2020.103504

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

103504

eissn

1532-0464

issn

1532-0480

pii

S1532-0464(20)30132-5

journal_volume

108

pub_type

杂志文章

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