ZA202202847B - Method for analyzing importance of disease risk factors based on mixed model - Google Patents

Method for analyzing importance of disease risk factors based on mixed model

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Publication number
ZA202202847B
ZA202202847B ZA2022/02847A ZA202202847A ZA202202847B ZA 202202847 B ZA202202847 B ZA 202202847B ZA 2022/02847 A ZA2022/02847 A ZA 2022/02847A ZA 202202847 A ZA202202847 A ZA 202202847A ZA 202202847 B ZA202202847 B ZA 202202847B
Authority
ZA
South Africa
Prior art keywords
risk factors
disease risk
mixed model
factors based
importance
Prior art date
Application number
ZA2022/02847A
Other languages
English (en)
Inventor
Li Jiahui
Zhu Jiajing
Liu Yongguo
Zhang Yun
Li Qiaoqin
Yang Shangming
Lu Xin
Original Assignee
Univ Electronic Sci & Tech China
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Univ Electronic Sci & Tech China filed Critical Univ Electronic Sci & Tech China
Publication of ZA202202847B publication Critical patent/ZA202202847B/en

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
ZA2022/02847A 2021-08-23 2022-03-09 Method for analyzing importance of disease risk factors based on mixed model ZA202202847B (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110965479.2A CN113707317B (zh) 2021-08-23 2021-08-23 一种基于混合模型的疾病危险因素重要性分析方法

Publications (1)

Publication Number Publication Date
ZA202202847B true ZA202202847B (en) 2022-06-29

Family

ID=78653864

Family Applications (1)

Application Number Title Priority Date Filing Date
ZA2022/02847A ZA202202847B (en) 2021-08-23 2022-03-09 Method for analyzing importance of disease risk factors based on mixed model

Country Status (2)

Country Link
CN (1) CN113707317B (zh)
ZA (1) ZA202202847B (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115378929A (zh) * 2022-10-26 2022-11-22 杭州华橙软件技术有限公司 多方案执行冲突的解决方法、系统、设备及存储介质
CN116738320A (zh) * 2023-06-30 2023-09-12 成都市双流区妇幼保健院 一种医疗保健大数据分析方法

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8490194B2 (en) * 2006-01-31 2013-07-16 Robert Moskovitch Method and system for detecting malicious behavioral patterns in a computer, using machine learning
CN109961851A (zh) * 2019-02-25 2019-07-02 南京理工大学 一种基于改进k均值聚类的疾病危险因素提取方法
CN110569883B (zh) * 2019-08-16 2023-03-31 淮阴工学院 基于Kohonen网络聚类和ReliefF特征选择的空气质量指数预测方法
CN111160635A (zh) * 2019-12-19 2020-05-15 金陵科技学院 一种基于ReliefF算法的区域物流需求影响因素预测方法

Also Published As

Publication number Publication date
CN113707317A (zh) 2021-11-26
CN113707317B (zh) 2023-04-07

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