| Title: |
An expert system for selecting wart treatment method |
| Authors: |
Khozeimeh, F.; Alizadehsani, R.; Roshanzamir, M.; Khosravi, A.; Layegh, P.; Nahavandi, S. |
| Contributors: |
Swinburne University of Technology |
| Source: |
Computers in Biology and Medicine, Vol. 81 (2017), pp. 167-175 |
| Publisher Information: |
Elsevier Ltd |
| Publication Year: |
2017 |
| Collection: |
Swinburne University of Technology: Swinburne Research Bank |
| Description: |
As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV) and may grow on all parts of body, especially hands and feet. There are several treatment methods for this illness. However, none of them can heal all patients. Consequently, physicians are looking for more effective and customized treatments for each patient. They are endeavoring to discover which treatments have better impacts on a particular patient. The aim of this study is to identify the appropriate treatment for two common types of warts (plantar and common) and to predict the responses of two of the best methods (immunotherapy and cryotherapy) to the treatment. As an original work, the study was conducted on 180 patients, with plantar and common warts, who had referred to the dermatology clinic of Ghaem Hospital, Mashhad, Iran. In this study, 90 patients were treated by cryotherapy method with liquid nitrogen and 90 patients with immunotherapy method. The selection of the treatment method was made randomly. A fuzzy logic rule-based system was proposed and implemented to predict the responses to the treatment method. It was observed that the prediction accuracy of immunotherapy and cryotherapy methods was 83.33% and 80.7%, respectively. According to the results obtained, the benefits of this expert system are multifold: assisting physicians in selecting the best treatment method, saving time for patients, reducing the treatment cost, and improving the quality of treatment. |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| Relation: |
http://hdl.handle.net/1959.3/473193; https://doi.org/10.1016/j.compbiomed.2017.01.001 |
| DOI: |
10.1016/j.compbiomed.2017.01.001 |
| Availability: |
http://hdl.handle.net/1959.3/473193; https://doi.org/10.1016/j.compbiomed.2017.01.001 |
| Rights: |
Copyright © 2017. |
| Accession Number: |
edsbas.812693A8 |
| Database: |
BASE |