Using Deep Learning to Mine the Key Factors of the Cost of AIDS Treatment
Liu, Dong1; Cao, Zhidong2; Li, Su1
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
专题复杂系统管理与控制国家重点实验室_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
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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