کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4943203 1437617 2017 31 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Joint discriminative and collaborative representation for fatty liver disease diagnosis
ترجمه فارسی عنوان
تشریک مساعی تشخیصی و همکاری برای تشخیص بیماری های کبدی چربی
کلمات کلیدی
کبد چرب، چند منظوره (وظیفه)، تصویر زبان، تصویر چهره، نمایندگی همکاری، نمایندگی تبعیض آمیز،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Many people suffer from the Fatty Liver disease due to the changes in diet and lifestyle, and the convenient diagnosis of it has attracted many attentions in recent years. The computerized tongue or facial diagnosis as an important diagnostic tool provides a possible way to detect the disease in the daily life. Most of existing approaches only takes a single modality (e.g., tongue or face) into account, although various modalities would contribute complementary information which is beneficial for the improvement of the diagnosis accuracy. To circumvent this issue, a novel multi-modal fusion method is presented in this paper. Particularly, a noninvasive capture device is first used to captured the tongue and facial images, followed by the feature extraction. Our so-called joint discriminative and collaborative representation approach is then proposed to not only reveal the correlation between the tongue and facial images, but also keep the discriminative representation of each class simultaneously. To optimize the proposed method, an efficient algorithm is proposed, obtaining a closed-form solution and greatly reducing the computation. In identification of the Fatty Liver Disease for healthy controls, the proposed multi-modal fusion approach achieves 85.10% in average accuracy and 0.9363 in the area under ROC curve, which obviously outperform the case of using a single modality and some state-of-the-art methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 89, 15 December 2017, Pages 31-40
نویسندگان
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