A method of electronic medical record similarity computation

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Abstract

With the development of electronic healthcare, more and more medical institutions begin to use the information system to manage their patient’s health records as well as other healthcare data. Electronic medical records (EMR) contain the patient’s personal information, medical history, clinical examination, treatment process, and other information, which have large research value. Today, enormous number of electronic medical records accumulated through the hospital information system all over the world. Analyzing these EMRs can effectively assist doctors in clinical decision-making, provide data support for clinical research as well as personalized healthcare service for patients. This paper presents a EMR similarity computation system. The system accepts EMRs collected from hospitals as input, go through a series of process, and eventually calculates the similarity of any two EMRs. An diseases classification experiment was designed to illustrate the effectiveness of the method. This system lays the foundation for further analysis of electronic medical records.

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He, Z., Yang, J., Wang, Q., & Li, J. (2017). A method of electronic medical record similarity computation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10219 LNCS, pp. 182–191). Springer Verlag. https://doi.org/10.1007/978-3-319-59858-1_18

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