Using Deep Learning to Mine the Key Factors of the Cost of AIDS Treatment
文献类型：会议论文
| 作者 | Liu, Dong1; Cao, Zhidong2 ; Li, Su1
|
| 出版日期 | 2017 |
| 会议日期 | June 26–27, 2017 |
| 会议地点 | Hong Kong, China |
| 英文摘要 | 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. |
| 会议录 | International Conference, ICSH 2017
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20171]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心 |
| 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]. 见:. Hong Kong, China. June 26–27, 2017. |
入库方式： OAI收割
来源：自动化研究所
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