Intelligent mining algorithm for complex medical data based on deep learning
- PDF / 2,197,358 Bytes
- 12 Pages / 595.276 x 790.866 pts Page_size
- 73 Downloads / 237 Views
ORIGINAL RESEARCH
Intelligent mining algorithm for complex medical data based on deep learning Xiaofeng Li1 · Dong Li2 · Yuanbei Deng3 · Jinming Xing4 Received: 13 December 2019 / Accepted: 17 June 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In order to address the problems of low precision, long time-consuming and low recall rate in mining complex attribute medical data in medical information, an intelligent mining algorithm for complex attribute medical data based on deep learning is proposed. Discretized medical data with complex attributes and converted it into a data type suitable for deep learning research, the convolutional neural network is used to analyze the association mapping relationship between complex attribute medical data sets and extract association rules of data. According to the degree of association between complex attribute medical data sets in multi-dimensional subspace to realize the effective mining of complex attribute medical data. The results show that the proposed algorithm takes less time and can extract association rules accurately, the data priority control efficiency is higher, the data mining accuracy is better, and the data mining recall rate is much higher than other methods, which verifies the feasibility of the proposed algorithm. Keywords Deep learning · Complex attributes · Medical data · Convolutional neural network · Association rules
1 Introduction With the rapid development of computer information technology in the current society, the construction of hospital informatization is becoming more and more mature. The initial hospital information system has gradually upgraded to the electronic medical record information system. The extensive use of this system has produced a large number of medical data. How to mine complex medical data intelligently is become an urgent problem in the medical industry (Ting et al. 2017; Hui et al. 2018). Nowadays, many data mining technologies have been widely used in banking, commerce, industry and other fields, and achieved remarkable results. Many experts and scholars have made some progress in the * Xiaofeng Li [email protected] 1
Department of Information Engineering, Heilongjiang International University, Harbin 150025, China
2
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
3
College of Mathematics and Econometrics, Hunan University, Changsha 410082, China
4
School of Physical Education, Northeast Normal University, Changchun 130024, China
research of medical data mining technology, but the field of medical information is facing difficulties such as fewer talents and poor academic skills, more difficulty in complex attributes of medical data mining, and a wide range of coverage, which greatly limits the application of mining technology in medical data (Pazhoumand 2018; Miholca et al. 2018). Therefore, it has important practical and theoretical significance for the research of data mining technology and its application in the medical field.
Data Loading...
