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An Introduction to Data Mining Applied to Health-Oriented Databases


Affiliations
1 Universidade Federal Fluminense (UFF), 25086-132, Duque de Caxias-RJ, Brazil
 

The application of data mining (DM) in healthcare is increasing. Healthcare organizations generate and collect large voluminous and heterogeneous information daily and DM helps to uncover some interesting patterns, which leads to the manual tasks elimination, easy data extraction directly from records, to save lives, to reduce the cost of medical services and to enable early detection of diseases. These patterns can help healthcare specialists to make forecasts, put diagnoses, and set treatments for patients in health facilities. This work overviews DM methods and main issues. Three case studies illustrate DM in healthcare applications: (i) In-Vitro Fertilization; (ii) Content-Based Image Retrieval (CBIR); and (iii) Organ transplantation.

Keywords

Data Mining, Healthcare Automation, Pattern Recognition, Computer Vision, Feature Extraction, Similarity Comparison.
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  • An Introduction to Data Mining Applied to Health-Oriented Databases

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Authors

M. A. De Jesus
Universidade Federal Fluminense (UFF), 25086-132, Duque de Caxias-RJ, Brazil
Vania V. Estrela
Universidade Federal Fluminense (UFF), 25086-132, Duque de Caxias-RJ, Brazil

Abstract


The application of data mining (DM) in healthcare is increasing. Healthcare organizations generate and collect large voluminous and heterogeneous information daily and DM helps to uncover some interesting patterns, which leads to the manual tasks elimination, easy data extraction directly from records, to save lives, to reduce the cost of medical services and to enable early detection of diseases. These patterns can help healthcare specialists to make forecasts, put diagnoses, and set treatments for patients in health facilities. This work overviews DM methods and main issues. Three case studies illustrate DM in healthcare applications: (i) In-Vitro Fertilization; (ii) Content-Based Image Retrieval (CBIR); and (iii) Organ transplantation.

Keywords


Data Mining, Healthcare Automation, Pattern Recognition, Computer Vision, Feature Extraction, Similarity Comparison.

References