Using Deep Learning to Mine the Key Factors of the Cost of AIDS Treatment

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Using Deep Learning to Mine the Key Factors of the Cost of AIDS Treatment
	Liu, Dong 1; Cao, Zhidong2 ; Li, Su 1
	2017
会议名称	International Conference, ICSH 2017
会议录名称	International Conference, ICSH 2017
会议日期	June 26–27, 2017
会议地点	Hong Kong, China
摘要	The medical burden of AIDS is a significant public health problem. However, it is affected by the multiple factors, among which there is yet some vague cognition, and further exploration is necessary. Thus, the artificial neural network (ANN) and restricted Boltzmann machine (RBM) be treated as the infrastructure of deep neural networks (DNN), mainly based on the features of demography, pathology and clinical manifestation of AIDS patient’s medical records to mine the impact factors of AIDS cost. And the proposed model could bring to light the previously uncharted latent knowledge and concepts. Based on reliable healthcare delivery, to inhibit the number of hospital days, intensive care and hospitalized frequency plus other sensitive factors, and avoid secondary infection and exposure to allergic reactions can obviously reduce the AIDS cost.
收录类别	EI
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/20171
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Cao, Zhidong
作者单位	1.Beijing Key Laboratory of Big Data Technology on Food Safety, Beijing Technology and Business University 2.State Key Laboratory of Complex Systems Management and Control, Institute of Automation, Chinese Academy of Sciences
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Liu, Dong,Cao, Zhidong,Li, Su. Using Deep Learning to Mine the Key Factors of the Cost of AIDS Treatment[C],2017.

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