Identifying Potential Clinical Syndromes of Hepatocellular Carcinoma Using PSO-Based Hierarchical Feature Selection Algorithm
المؤلفون المشاركون
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-03-17
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors.
Clinical symptoms attributable to HCC are usually absent, thus often miss the best therapeutic opportunities.
Traditional Chinese Medicine (TCM) plays an active role in diagnosis and treatment of HCC.
In this paper, we proposed a particle swarm optimization-based hierarchical feature selection (PSOHFS) model to infer potential syndromes for diagnosis of HCC.
Firstly, the hierarchical feature representation is developed by a three-layer tree.
The clinical symptoms and positive score of patient are leaf nodes and root in the tree, respectively, while each syndrome feature on the middle layer is extracted from a group of symptoms.
Secondly, an improved PSO-based algorithm is applied in a new reduced feature space to search an optimal syndrome subset.
Based on the result of feature selection, the causal relationships of symptoms and syndromes are inferred via Bayesian networks.
In our experiment, 147 symptoms were aggregated into 27 groups and 27 syndrome features were extracted.
The proposed approach discovered 24 syndromes which obviously improved the diagnosis accuracy.
Finally, the Bayesian approach was applied to represent the causal relationships both at symptom and syndrome levels.
The results show that our computational model can facilitate the clinical diagnosis of HCC.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ji, Zhiwei& Wang, Bing. 2014. Identifying Potential Clinical Syndromes of Hepatocellular Carcinoma Using PSO-Based Hierarchical Feature Selection Algorithm. BioMed Research International،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-447817
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ji, Zhiwei& Wang, Bing. Identifying Potential Clinical Syndromes of Hepatocellular Carcinoma Using PSO-Based Hierarchical Feature Selection Algorithm. BioMed Research International No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-447817
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ji, Zhiwei& Wang, Bing. Identifying Potential Clinical Syndromes of Hepatocellular Carcinoma Using PSO-Based Hierarchical Feature Selection Algorithm. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-447817
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-447817
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر