DocumentCode
1604435
Title
Bioinformatic System Modeling on Hetian Uygur Natural Longevity People
Author
Sun, Shangshang ; Zhang, Xiaohui ; Zhang, Yanchi ; Wang, Haiyun ; Yu, Yongsui ; Zhang, Mingjiang
Author_Institution
Coll. of Electr. Eng., Xinjiang Univ.
fYear
2006
Firstpage
813
Lastpage
816
Abstract
Longevity and life science are active topics in biomedicine and other subjects. In this research, longevity people from Hetian area in Xinjiang, China are used as an example. The cause of longevity is discussed and a bioinformatic longevity model is established based on the medical findings. Human life is a complex multi-variant natural process. It is complicated yet important to extract expert knowledge that can describe the interactions among different factors and influence of the factors on human life. Artificial intelligent (AI) and information processing techniques are used to efficiently process large amount of collected biomedical data and effectively extract hidden information into the longevity model. The test results show that the established model is able to identify individuals who belong to longevity group with over 90 percent accuracy. This research creates a new approach to explore the cause of formation of human longevity based on comprehensive medical data rather than just from one medical subject. More importantly, this research explores a practical way to model complex bioinformatic systems
Keywords
artificial intelligence; medical computing; physiological models; Hetian Uygur natural longevity people; artificial intelligent; bioinformatic system modeling; biomedicine; extract expert knowledge; human life; information processing; life science; Artificial intelligence; Bioinformatics; Cardiac disease; Cardiovascular diseases; Data mining; Humans; Information processing; Modeling; Neoplasms; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1616539
Filename
1616539
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