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The aim is to distinguish between the presence and absence of cardiac arrhythmia and to classify it in one of the 16 groups:
- Class 01 refers to 'normal' ECG
- Classes 02 to 15 refers to different classes of arrhythmia
- Class 16 refers to the rest of unclassified ones.
For the time being, there exists a computer program that makes such a classification. However there are differences between the cardiolog's and the programs classification. Taking the cardiolog's as a gold standard we aim to minimise this difference by means of machine learning tools.
This is one of three domains provided by the Oncology Institute that has repeatedly appeared in the machine learning literature. (See also lymphography and primary-tumor.)
This data set includes 201 instances of one class and 85 instances of another class. The instances are described by 9 attributes, some of which are linear and some are nominal.
This model describes the healthy life expectancy as a result of the investment in health resources.
Data extracted from UNdata
This model tries to predict whether a hepatitis patient will live or die
100 volunteers provide a semen sample analyzed according to the WHO 2010 criteria. Sperm concentration are related to socio-demographic data, environmental factors, health status, and life habits.
David Gil, dgil '@' dtic.ua.es, Lucentia Research Group, Department of Computer Technology, University of Alicante
Jose Luis Girela, girela '@' ua.es, Department of Biotechnology, University of Alicante
Cause of death in USA prediction based in deaths in the age ranges
Car accidents in UK during 2012.