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基于机器学习的实时医疗健康数据挖掘系统的实现。

Implementation of Real-Time Medical and Health Data Mining System Based on Machine Learning.

机构信息

Zhengzhou University of Light Industry, Engineering Training Center, Zhengzhou 450001, Henan, China.

The Second Affiliated Hospital of Zhengzhou University, Radiology Department, Zhengzhou 450000, Henan, China.

出版信息

J Healthc Eng. 2021 Nov 19;2021:7011205. doi: 10.1155/2021/7011205. eCollection 2021.

DOI:10.1155/2021/7011205
PMID:34840702
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8626197/
Abstract

This article analyzes the application process of data mining technology in the medical and health management system and uses machine learning algorithms to design a medical and health data mining system. The system collects patient's physical health data based on wireless sensing technology and uses machine learning algorithms to analyze the data. The system uploads the collected health data to the system for cluster analysis. Finally, the method is applied to the diagnosis data mining of patients, so as to prove the effectiveness of the classification method in the medical field through examples.

摘要

本文分析了数据挖掘技术在医疗健康管理系统中的应用过程，利用机器学习算法设计了一个医疗健康数据挖掘系统。该系统基于无线传感技术采集患者的身体健康数据，利用机器学习算法对数据进行分析。系统将采集到的健康数据上传到系统中进行聚类分析。最后，将该方法应用于患者的诊断数据挖掘中，通过实例证明了该分类方法在医学领域的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/bf9e5cf1e53d/JHE2021-7011205.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/8e65b3352ad3/JHE2021-7011205.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/fb67b8d4a20d/JHE2021-7011205.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/bf9e5cf1e53d/JHE2021-7011205.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/8e65b3352ad3/JHE2021-7011205.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/fb67b8d4a20d/JHE2021-7011205.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d0/8626197/bf9e5cf1e53d/JHE2021-7011205.003.jpg

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Sci Rep. 2021 Sep 23;11(1):18961. doi: 10.1038/s41598-021-98387-w.
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Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey.深度学习在智能医疗系统中多等级脑肿瘤分类中的应用：前瞻性调查。
IEEE Trans Neural Netw Learn Syst. 2021 Feb;32(2):507-522. doi: 10.1109/TNNLS.2020.2995800. Epub 2021 Feb 4.
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Deep learning in mental health outcome research: a scoping review.
深度学习在精神健康结局研究中的应用：范围综述。
Transl Psychiatry. 2020 Apr 22;10(1):116. doi: 10.1038/s41398-020-0780-3.
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Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.使用深度学习量化心理治疗内容与临床结果之间的关联。
JAMA Psychiatry. 2020 Jan 1;77(1):35-43. doi: 10.1001/jamapsychiatry.2019.2664.
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A systematic literature review of machine learning in online personal health data.机器学习在在线个人健康数据中的系统文献综述。
J Am Med Inform Assoc. 2019 Jun 1;26(6):561-576. doi: 10.1093/jamia/ocz009.
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A call for deep-learning healthcare.对深度学习医疗保健的呼吁。
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