Data Mining and Association Analysis of Irrational Use of Antibiotics in Outpatient Data of New Cooperative Medical System

2019 ◽  
pp. 36-42
Author(s):  
Qingshun Hu ◽  
Xiaoqiang Ren
Keyword(s):  
Data Mining ◽  
Association Analysis ◽  
Medical System

scholarly journals ПРОГНОЗУВАННЯ ТА ПРИЙНЯТТЯ РІШЕНЬ В УМОВАХ НЕВИЗНАЧЕНОСТІ В ПРОБЛЕМАХ СИСТЕМНИХ МЕДИЧНИХ ДОСЛІДЖЕНЬ

2017 ◽  
Author(s):  
V. P. Martsenyuk ◽  
I Ye. Andrushchak
Keyword(s):  
Data Mining ◽  
Support System ◽  
System Analysis ◽  
Medical System ◽  
Information Support ◽  
System Research ◽  
Data Mining Algorithms ◽  
Analysis Methods ◽  
Mining Algorithms ◽  
Information Support System

The work presents our results in field of application of system analysis methods to problem of medical research. We emphasize effects of uncertainty that should be taken into account in such complex processes. Medical system research requires information support system implementing data mining algorithms resulting in decision trees or IF-THEN rules. Besides that such system should be object-oriented and web-integrated.The aim of this study was to develop information support system based on data mining algorithms applied to system analysis method for medical system research. System analysis methods were used for qualitative analysis of diseases mathematical models. Algorithms such as decision tree induction and sequential covering algorithm were applied for data mining from learning data set.We observed the complex qualitative behavior of population and diseases models depending on parameters and controllers even without considering probabilistic nature of the most of quantities and parameters of information models.

Association analysis for quantitative traits by data mining: QHPM

2002 ◽  
Vol 66 (6) ◽  
pp. 419-429 ◽  
Author(s):  
P. ONKAMO ◽  
V. OLLIKAINEN ◽  
P. SEVON ◽  
H. T. T. TOIVONEN ◽  
H. MANNILA ◽  
...  
Keyword(s):  
Data Mining ◽  
Association Analysis ◽  
Quantitative Traits

scholarly journals Knowledge Discovery from Healthcare Electronic Records for Sustainable Environment

2021 ◽  
Vol 13 (16) ◽  
pp. 8900
Author(s):  
Naeem Ahmed Mahoto ◽  
Asadullah Shaikh ◽  
Mana Saleh Al Reshan ◽  
Muhammad Ali Memon ◽  
Adel Sulaiman
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Association Analysis ◽  
Pattern Mining ◽  
Large Data ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Electronic Records ◽  
Data Mining Techniques ◽  
Healthcare Data

The medical history of a patient is an essential piece of information in healthcare agencies, which keep records of patients. Due to the fact that each person may have different medical complications, healthcare data remain sparse, high-dimensional and possibly inconsistent. The knowledge discovery from such data is not easily manageable for patient behaviors. It becomes a challenge for both physicians and healthcare agencies to discover knowledge from many healthcare electronic records. Data mining, as evidenced from the existing published literature, has proven its effectiveness in transforming large data collections into meaningful information and knowledge. This paper proposes an overview of the data mining techniques used for knowledge discovery in medical records. Furthermore, based on real healthcare data, this paper also demonstrates a case study of discovering knowledge with the help of three data mining techniques: (1) association analysis; (2) sequential pattern mining; (3) clustering. Particularly, association analysis is used to extract frequent correlations among examinations done by patients with a specific disease, sequential pattern mining allows extracting frequent patterns of medical events and clustering is used to find groups of similar patients. The discovered knowledge may enrich healthcare guidelines, improve their processes and detect anomalous patients’ behavior with respect to the medical guidelines.

A Survey of Predicting Heart Disease

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
M Preethi ◽  
J Selvakumar
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Cardiovascular Disease ◽  
Heart Disease ◽  
Medical System ◽  
Learning Models ◽  
Clinical Area ◽  
Survey Paper ◽  
Critical Challenge ◽  
Machine Learning Models

This paper describes various methods of data mining, big data and machine learning models for predicting the heart disease. Data mining and machine learning plays an important role in building an important model for medical system to predict heart disease or cardiovascular disease. Medical experts can help the patients by detecting the cardiovascular disease before occurring. Now-a-days heart disease is one of the most significant causes of fatality. The prediction of heart disease is a critical challenge in the clinical area. But time to time, several techniques are discovered to predict the heart disease in data mining. In this survey paper, many techniques were described for predicting the heart disease.

Research and Application of Data Mining(DM) in the Analysis of Postgraduate Admission Information

2014 ◽  
Vol 687-691 ◽  
pp. 1254-1257
Author(s):  
Hui Hui
Keyword(s):  
Data Mining ◽  
Cluster Analysis ◽  
Empirical Research ◽  
Association Analysis ◽  
Strong Support ◽  
Admission Data ◽  
Knowledge Theory ◽  
And Cluster Analysis

By applying the DM technologies such as Association analysis and Cluster analysis, this paper has made systematic empirical research combined with the postgraduate admission data of the key College C in Beijing, and also made description and analysis of the mining results. This paper has applied the DM method and knowledge theory in practice, which has offered strong support for the postgraduate admission management of College C.

The Association Analysis of Technical Indicators of Shanghai Stock Market

2014 ◽  
Vol 651-653 ◽  
pp. 1651-1654
Author(s):  
Rui Zhong Wang
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Stock Market ◽  
Success Rate ◽  
Association Analysis ◽  
Association Rules ◽  
Technical Indicators ◽  
Use Of Data ◽  
Stock Market Investors ◽  
The Relationship

This paper selected as part of a number of technical indicators, the main use of data mining software for different technical indicators signal given trading technical analysis of association rules. By studying the resulting characteristics of the relationship between the rules and give the stock market investors a certain decision support, to enable investors to operate with a higher success rate.

Sign in / Sign up

Export Citation Format

Share Document