A Nearest Neighbor Multi-Granularity Profit Method for Collaborative Reduction of Large-Scale Electronic Health Record Knowledge
A health record and large-scale technology, applied in the field of intelligent processing of medical information, can solve problems such as missing data, incompleteness, and impact on intelligent auxiliary diagnosis decisions, and achieve the effect of reducing execution time, reducing complexity cost, and improving accuracy
Active Publication Date: 2022-04-29
南通大学技术转移中心有限公司
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Problems solved by technology
However, the data in large-scale electronic health records often presents a high degree of incompleteness, and there is a considerable proportion of missing data in established electronic health records.
In addition, the values of some attribute columns of electronic health record data are described in descriptive language, which has strong ambiguity. If all fuzzy data are directly converted into numerical or symbolic data, a large amount of electronic health record information may be lost. Even affect the follow-up intelligent auxiliary diagnosis decision
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[0066] The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention.
[0067] Such as Figure 1-2 As shown, the present invention discloses a nearest neighbor multi-granularity profit method for collaborative reduction of large-scale electronic health record knowledge, including the following steps:
[0068] A. Segment large-scale electronic health record datasets into different multi-granularity evolutionary subpopulations Granu-Subpopulation on the big data Spark cloud platform i Among them, i=1,2,…,N, N is the total number of multi-granularity evolutionary subpopulations, so the task of knowledge reduction of large-scale electronic health records data set is decompose...
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The invention discloses a nearest-neighbor multi-granularity profit method for collaborative reduction of large-scale electronic health record knowledge. First, the large-scale electronic health record data set is divided into different multi-granularity evolutionary subpopulations on the Spark cloud platform; Construct a multi-granularity profit model based on the nearest neighbor, and construct a collaborative nearest neighbor vector in the nearest neighbor radius; then find the shared nearest neighbor profit weight of the super elite and its weight profit vector, and perform the self-adaptation of the super elite weight profit matrix Dynamically adjust the strategy; finally obtain the large-scale electronic health record data knowledge collaborative reduction set and its core attributes, and store the electronic health record knowledge reduction set to the Spark cloud platform. The invention can efficiently obtain incomplete and fuzzy data knowledge reduction sets in large-scale electronic health records, and has great significance and value for decision support analysis of electronic health records.
Description
technical field [0001] The invention relates to the field of intelligent processing of medical information, in particular to a nearest neighbor multi-granularity profit method for collaborative reduction of large-scale electronic health record knowledge. Background technique [0002] The "Healthy China 2020" strategic plan mentioned: "my country will establish a relatively complete basic medical and health system covering urban and rural residents, realize the goal of everyone enjoying basic medical and health services, promote the equalization of health service utilization, and greatly increase the The health level of the whole people; in terms of health informatization, it is necessary to establish a system for the use and management of electronic health records covering urban and rural residents." [0003] Electronic health records are personal health electronic historical records formed when people are engaged in medical and health-related activities and have the value of...
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IPC IPC(8): G16H10/60G06N3/00
CPCG16H10/60G06N3/006
Inventor 丁卫平孙颖李铭鞠恒荣冯志豪曹金鑫张毅任龙杰丁帅荣陈森博万杰赵理莉
Owner 南通大学技术转移中心有限公司