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Comparison of coronary artery disease guidelines with extracted knowledge from data mining
Peyman Rezaei-Hachesu1, Azadeh Oliyaee2, Naser Safaie3
1Health Information Technology Department, School of Management and Medical Informatics, Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Insights
Coronary artery disease (CAD) risk factors, including chest pain and age over 54 in males, were identified using data mining. Blood tests emerged as a highly valuable diagnostic tool for CAD patients.
Area of Science:
- Cardiology
- Data Mining
- Health Informatics
Background:
- Coronary artery disease (CAD) is a leading global cause of mortality and disability.
- Up-to-date national guidelines are crucial for managing heart-related diseases effectively.
- Data mining offers a powerful approach to uncover insights from patient data.
Purpose of the Study:
- To identify significant risk factors and diagnostic patterns for Coronary Artery Disease (CAD) using data mining.
- To compare data mining-derived knowledge with established Canadian Cardiovascular Society (CCS) and US National Institute of Health (NIH) guidelines.
- To rank the importance of risk factors and diagnostic methods based on local patient data.
Main Methods:
- Analysis of 1993 completed patient records with CAD from 2009-2014.
- Utilized 25 variables, including CAD status and 24 predictor variables, for knowledge discovery.
- Compared extracted data mining rules with CCS and NIH guidelines, ranking findings by importance.
Main Results:
- Chest pain was identified as the most significant factor influencing CAD.
- Elderly males (age >54) showed a high probability of CAD diagnosis.
- Blood tests demonstrated greater diagnostic value compared to other recommended medical tests.
Conclusions:
- Data mining techniques confirm and enhance existing CAD guidelines by ranking risk factors.
- Extracted knowledge revealed novel patterns in CAD patient data.
- The study validates the utility of comparing data mining results with established clinical guidelines.
Abstract:
Coronary artery disease (CAD) is one of the major causes of disability and death in the world. Accordingly utilizing from a national and update guideline in heart-related disease are essential. Finding interesting rules from CAD data and comparison with guidelines was the objectives of this study. In this study 1993 valid and completed records related to patients (from 2009 to 2014) who had suffered from CAD were recruited and analyzed. Total of 25 variable including a target variable (CAD) and 24 inputs or predictor variables were used for knowledge discovery. To perform comparison between extracted knowledge and well trusted guidelines, Canadian Cardiovascular Society (CCS) guideline and US National Institute of Health (NIH) guideline were selected. Results of valid datamining rules were compared with guidelines and then were ranked based on their importance. The most significant factor influencing CAD was chest pain. Elderly males (age >54) have a high probability to be diagnosed with CAD. Diagnostic methods that are listed in guidelines were confirmed and ranked based on analyzing of local CAD patients data. Knowledge discovery revealed that blood test has more diagnostic value among other medical tests that were recommended in guidelines. Guidelines confirm the achieved results from data mining (DM) techniques and help to rank important risk factors based on national and local information. Evaluation of extracted rules determined new patterns for CAD patients.
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