کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6921193 864461 2015 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Exploring the color feature power for psoriasis risk stratification and classification: A data mining paradigm
ترجمه فارسی عنوان
بررسی ویژگی قدرت رنگ برای طبقه بندی و دسته بندی خطر پسوریازیس: پارادایم داده کاوی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Using a fixed data size of 540 images with equal number of healthy and diseased, 10 fold cross-validation protocol, and SVM of polynomial kernel of type two, pCAD system shows an accuracy of 99.94% with sensitivity and specificity of 99.93% and 99.96%. Using a varying data size protocol, the mean classification accuracies for color, grayscale, and combined scenarios are: 92.85%, 93.83% and 93.99%, respectively. The reliability of the system in these three scenarios are: 94.42%, 97.39% and 96.00%, respectively. We conclude that pCAD system using color space alone is compatible to grayscale space or combined color and grayscale spaces. We validated our pCAD system against facial color databases and the results are consistent in accuracy and reliability.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 65, 1 October 2015, Pages 54-68
نویسندگان
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