Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/2511
Title: | User Awareness System to Diagnose Dermatological Diseases |
Authors: | Chandrasiri, S Weerasooriya, T Pathivarathan, V Thavabalasingham, N Philipreman, K Gunasekaran, S |
Keywords: | Dermatological diseases Image processing Data mining Web scraping Natural Language Processing |
Issue Date: | 18-Dec-2020 |
Publisher: | Foundation of Computer Science |
Series/Report no.: | International Journal of Computer Applications;Vol 175 Issue 36 Pages 30-35 |
Abstract: | Nowadays, humans' health is deteriorating by dermatological diseases, and the spreading rate is high. Most people are not aware of skin diseases. As they do not realize these diseases' seriousness, they try to treat with some remedies by themselves, even without knowing what the actual disease is. Nevertheless, it is not a suitable way to cure the disease, leading to future complications. So still the dermatological diseases remain as one of the main categories of common health issues. A few people prefer to use computerized systems to evaluate the disease conditions these days. Moreover, it is essential to know about the diseases to manage that condition and prevent escalation. Therefore, the proposed system is implemented to give users some knowledge about dermatological diseases as much as possible. The users can get awareness and predict skin diseases and complications from the data mining technique. The user can identify the stage of the dermatological disease by applying the classification algorithm. Furthermore, this system will also scrap web pages related to that disease from known or system verified websites. The content analysis is based on the machine learning process, especially using Neural Language Processing. Hence, the system will undeniably be useful to the users to summarize skin diseases and get concerns from a dermatologist |
URI: | http://rda.sliit.lk/handle/123456789/2511 |
ISSN: | (0975 – 8887 |
Appears in Collections: | Research Papers - Open Access Research Research Papers - SLIIT Staff Publications Research Publications -Dept of Information Technology |
Files in This Item:
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skidec.pdf | 682.85 kB | Adobe PDF | View/Open |
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