Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model
المؤلفون المشاركون
Zhang, Ying
Liang, Wenbin
Zou, Xianchun
Chen, Hongling
Gao, Mingyan
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-05-13
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Today, it has become a hot issue in cancer research to make precise prognostic prediction for breast cancer patients, which can not only effectively avoid overtreatment and medical resources waste, but also provide scientific basis to help medical staff and patients family members to make right medical decisions.
As well known, cancer is a partly inherited disease with various important biological markers, especially the gene expression profile data and clinical data.
Therefore, the accuracy of prediction model can be improved by integrating gene expression profile data and clinical data.
In this paper, we proposed an end-to-end model, Attention-based Multi-NMF DNN (AMND), which combines clinical data and gene expression data extracted by Multiple Nonnegative Matrix Factorization algorithms (Multi-NMF) for the prognostic prediction of breast cancer.
The innovation of this method is highlighted through using clinical data and combining multiple feature selection methods with the help of Attention mechanism.
The results of comprehensive performance evaluation show that the proposed model reports better predictive performances than either models only using data of single modality, e.g., gene or clinical, or models based on any single NMF improved methods which only use one of the NMF algorithms to extract features.
The performance of our model is competitive or even better than other previously reported models.
Meanwhile, AMND can be extended to the survival prediction of other cancer diseases, providing a new strategy for breast cancer prognostic prediction.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Hongling& Gao, Mingyan& Zhang, Ying& Liang, Wenbin& Zou, Xianchun. 2019. Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model. BioMed Research International،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1128601
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Hongling…[et al.]. Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model. BioMed Research International No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1128601
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Hongling& Gao, Mingyan& Zhang, Ying& Liang, Wenbin& Zou, Xianchun. Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model. BioMed Research International. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1128601
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1128601
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