Bioinformatic system modeling on hetian uygur natural longevity people
- Resource Type
- Authors
- Shangshang Sun; Yongsui Yu; Mingjiang Zhang; Yanchi Zhang; Xiaohui Zhang; Haiyun Wang
- Source
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2006
- Subject
- Engineering
Process (engineering)
business.industry
Human life
media_common.quotation_subject
Medical findings
Information processing
Longevity
Systems modeling
Data science
Natural (music)
business
Biomedicine
media_common
- Language
- ISSN
- 1557-170X
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.