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Dimensionality Reduction in Complex Medical Data: Improved Self-Adaptive Niche Genetic Algorithm
المؤلفون المشاركون
Yan, Jing
Zhu, Min
Xia, Jing
Yan, Molei
Cai, Guolong
Ning, Gangmin
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-11-16
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
With the development of medical technology, more and more parameters are produced to describe the human physiological condition, forming high-dimensional clinical datasets.
In clinical analysis, data are commonly utilized to establish mathematical models and carry out classification.
High-dimensional clinical data will increase the complexity of classification, which is often utilized in the models, and thus reduce efficiency.
The Niche Genetic Algorithm (NGA) is an excellent algorithm for dimensionality reduction.
However, in the conventional NGA, the niche distance parameter is set in advance, which prevents it from adjusting to the environment.
In this paper, an Improved Niche Genetic Algorithm (INGA) is introduced.
It employs a self-adaptive niche-culling operation in the construction of the niche environment to improve the population diversity and prevent local optimal solutions.
The INGA was verified in a stratification model for sepsis patients.
The results show that, by applying INGA, the feature dimensionality of datasets was reduced from 77 to 10 and that the model achieved an accuracy of 92% in predicting 28-day death in sepsis patients, which is significantly higher than other methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhu, Min& Xia, Jing& Yan, Molei& Cai, Guolong& Yan, Jing& Ning, Gangmin. 2015. Dimensionality Reduction in Complex Medical Data: Improved Self-Adaptive Niche Genetic Algorithm. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057999
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhu, Min…[et al.]. Dimensionality Reduction in Complex Medical Data: Improved Self-Adaptive Niche Genetic Algorithm. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057999
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhu, Min& Xia, Jing& Yan, Molei& Cai, Guolong& Yan, Jing& Ning, Gangmin. Dimensionality Reduction in Complex Medical Data: Improved Self-Adaptive Niche Genetic Algorithm. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057999
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1057999
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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