Education, Science, Technology, Innovation and Life
Open Access
Sign In

Design and Implementation of Scientific Research Data Platform Based on Psychiatric Big Data

Download as PDF

DOI: 10.23977/jnca.2019.41004 | Downloads: 16 | Views: 1287


Feng Gao 1, Wei Zhong 1, Xinlei Chen 1, Guangzhong Yin 1


1 Suzhou GuangJi Hospital, Suzhou 215137, Jiangsu, China

Corresponding Author

Wei Zhong


Health care big data is an important basic strategic resource of the country. The application of medical big data is of great significance for clinical medical research, scientific management and the transition and development of medical service mode. Regarding the mining and research of big data in psychiatry, there is no corresponding research in China and abroad. Establish a clinical data center system: collect all the data of the hospital's clinical information system, including structured data and pathological reports in text format, scans of past medical records, etc. The main function of such system is to clean, store and refactor data for clinical and scientific analysis with the common data model (Common Data Mode1) as the core. In this article, in order to illustrating design and implementation of such system, architecture design, key technology and implementation steps are introduced in detail as well as the safety and reliability. Relied on the big data mining and analysis technology of electronic medical records, in the future, a clinical data center system would be applied to clinical medicine, scientific research data support, and guiding treatment programs.


Psychiatry, Big data, Research platform


Feng Gao, Wei Zhong, Xinlei Chen and Guangzhong Yin, Design and Implementation of Scientific Research Data Platform Based on Psychiatric Big Data. Journal of Network Computing and Applications (2019) 4: 21-25. DOI:


[1] Istephan S, Siadat M R. Extensible Query Framework for Unstructured Medical Data -- A Big Data Approach [C]// IEEE International Conference on Data Mining Workshop. IEEE, 2016.
[2] Zhang T, Chi H, Ouyang Z. Detecting Research Focus and Research Fronts in the Medical Big Data Field Using Co-word and Co-citation Analysis [C] // 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2018.
[3] Mavroeidakos T, Tsolis N, Vergados D D. Centralized management of medical big data in Intensive Care Unit: A security analysis [C] // Smart Cloud Networks & Systems. IEEE, 2017.
[4] Shah F, Li J P, Shah F, et al. Quality Compression for Medical Big Data X-Ray Image using Biorthogonal 5.5 Wavelet[J]. International Journal of Engineering Research and Applications, 2016.
[5] Ishikawa K B. Medical Big Data for Research Use: Current Status and Related Issues [J]. Japan Medical Association Journal, 2016, 59 (2): 110-124.
[6] Windridge D, Bober M. A Kernel-Based Framework for Medical Big-Data Analytics [M] // Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. Springer Berlin Heidelberg, 2014.
[7] Yao Q, Tian Y, Li P F, et al. Design and Development of a Medical Big Data Processing System Based on Hadoop [J]. Journal of Medical Systems, 2015, 39 (3): 23.
[8] Flynn F V. Medical Data Processing [J]. Proceedings of the Royal Society of Medicine, 1977, 70 (10): 750.
[9] Hiden H, Woodman S, Watson P. Prediction of workflow execution time using provenance traces: Practical applications in medical data processing [C] // 2016 IEEE 12th International Conference on e-Science (e-Science). IEEE, 2016.
[10] Csaba Horváth, Gábor Fodor, Ferenc Kovács, et al. A Proposed Scalable Environment for Medical Data Processing and Evaluation [J]. 2010.
[11] Popov A A, Yanenko V M, Zaitsev N G, et al. Automated system for medical data processing. [J]. International Journal of Bio-Medical Computing, 1970, 1 (3): 193-209.
[12] Xue J, Tian J, Dai Y K, et al. Processing Framework and the Fast Volume Rendering Algorithms for Out- of-Core Medical Data [J]. Journal of Software, 2009, 19 (12): 3237-3248.
[13] Asvestas P A, Matsopoulos G K, Nikita K S. Applications of fractal theory on medical data processing. [M]// Декабристы и их время /. Изд-во МГУ, 2000.
[15] Satoh H, Niki N, Takahashi E, et al. Teleradiology mobile internet system and home care medical system with a new information security solution [C] // SPIE Medical Imaging. 2015.

Downloads: 869
Visits: 67029

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.