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Imaging Studies for Cardiovascular System V: CT01:28

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Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
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Systematic mapping study of data mining-based empirical studies in cardiology.

Ilham Kadi, Ali Idri1, José Luis Fernandez-Aleman2

  • 1Mohammed V University in Rabat, Morocco.

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Summary

This study maps data mining applications in cardiology, revealing its growing use to extract knowledge and aid decision-making for patients and healthcare professionals.

Keywords:
cardiologydata miningknowledge extractionmapping studymedical tasks

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Area of Science:

  • Cardiology
  • Medical Informatics
  • Data Science

Background:

  • Data mining transforms large datasets into actionable information for decision-making.
  • Its application is rapidly expanding within the medical field, especially in cardiology.
  • Data mining offers significant benefits to patients, cardiologists, and nurses.

Purpose of the Study:

  • To systematically map and synthesize empirical studies on data mining in cardiology.
  • To analyze trends and patterns in data mining research within cardiology from 2000-2015.

Main Methods:

  • Systematic mapping study methodology.
  • Selection and analysis of 142 articles published between 2000 and 2015.
  • Categorization based on publication year/channel, research type, medical task, and empirical type.

Main Results:

  • Identified trends in data mining techniques applied to cardiology.
  • Analyzed the evolution of data mining research in cardiology over the 15-year period.
  • Synthesized empirical evidence on the impact of data mining in cardiovascular medicine.

Conclusions:

  • Data mining is a valuable tool in modern cardiology.
  • Recommendations are provided for future research and clinical application.
  • Highlights the potential for enhanced patient care and medical decision-making through data mining.