Potential Level Detection of Skin Cancer with Expert System Using Forward Chaining and Certainty Factor Method

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI:10.1109/IOTAIS.2018.8600855

Reinaldi Nur Pranata, A. Osmond, C. Setianingsih

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引用次数: 5

Abstract

Skin cancer is the abnormal growth of skin cells that can not be controlled. Skin cancer appears when the DNA is damaged skin cells (mostly due to ultraviolet radiation from the sun) triggers mutations that skin cells grow rapidly, can not be controlled and start forming a tumor. Skin cancer can be overcome if it is detected earlier before spreading or doing metastasis. However, the tendency of people who are indifferent and reluctant to check or consult with doctors make his condition worse without realizing it. Therefore, designed an application for Skin Cancer Detection with Image Processing and Expert System using Forward Chaining and Certainty Factor method. The end result of image processing and expert system in this application is the assessment of High Risk, Low Risk, or Medium Risk of nevus conditions in patients. With the design of this system is expected to help raise awareness to detect early skin cancer. The results in this study show that the application has an accuracy rate of 100%. It shows that this system produces the same results as an expert.

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基于正向链和确定性因子法的专家系统皮肤癌潜在水平检测

皮肤癌是皮肤细胞无法控制的异常生长。当皮肤细胞的DNA受损(主要是由于来自太阳的紫外线辐射)引发突变，皮肤细胞迅速生长，无法控制并开始形成肿瘤时，皮肤癌就出现了。如果在扩散或转移之前及早发现，皮肤癌是可以治愈的。然而，人们的冷漠和不愿检查或咨询医生的倾向使他的病情在不知不觉中恶化。因此，采用前向链法和确定性因子法设计了一种基于图像处理和专家系统的皮肤癌检测应用。在此应用中，图像处理和专家系统的最终结果是对患者的痣状况进行高风险，低风险或中等风险的评估。该系统的设计有望帮助提高人们对早期皮肤癌的认识。本研究结果表明，该应用程序具有100%的准确率。结果表明，该系统产生的结果与专家相同。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)

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