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Rule Based Medicine Recommendation for Skin Diseases Using Ontology with Semantic Information
6th International Conference on Advances in Computing and Data Sciences, ICACDS 2022 ; 1613 CCIS:373-387, 2022.
Article in English | Scopus | ID: covidwho-2013951
ABSTRACT
Generally, skin diseases are taken seriously only after it gets aggravated. Many patients do not feel comfortable to consult physician for their skin problems and try to cure with home remedies. Identifying good dermatologist is more challenging. Disease gets cured with ease, if treated properly otherwise it becomes complicated. To handle this, knowledge-based decision support system is developed which provide recommendation for treatment. System realizes patient’s symptoms with location, cause and recommends appropriate medicines. Ontology is used to elaborate data concepts and their relationships in skin disease, which permits sharing and reuse of domain knowledge. Semantics described using Web Ontology Language (OWL) with vocabularies, resources, logic’s, and inference rules are queried for relevant information through SPARQL. System proved to render most valuable service to skin patients with ease and accuracy of its recommendation is high. It renders best treatment in COVID situation where people’s movement is restricted to great extent. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 6th International Conference on Advances in Computing and Data Sciences, ICACDS 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 6th International Conference on Advances in Computing and Data Sciences, ICACDS 2022 Year: 2022 Document Type: Article