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| Mapping and Migration of Medical and Health Big Data with SNOMED CT |
| Chen Donghua1, Zhang Runtong1, Fu Lei2, Shang Xiaopu1, Zhu Xiaomin3 |
1. School of Economics and Management, Beijing Jiaotong University, Beijing 100044;
2. Core Laboratory of Translational Medicine, Chinese PLA General Hospital, Beijing 100853;
3. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044 |
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Abstract This paper reports the application of the core system of Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT) to the analyzing process of medical and health big data, and proposes a mapping and migration approach through SNOMED CT. The system provides reference of relevant processes, models, and algorithms to analyze medical and health big data effectively. First, the implicit relationships between the data and SNOMED CT are analyzed. Then, through the use of the SNOMED CT, four stages in our method are illustrated; evaluating the mapping requirement, establishing the mapping model, verifying the model, and maintaining the model. Finally, we use a real mapping case of big data to demonstrate the feasibility of the proposed method. By examining the complex medical concepts and their semantic relationship set in SNOMED CT, our proposed method promotes deeper mining of knowledge from existing medical and health big data, which holds great significance for the development of medical informatics.
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Received: 15 November 2017
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