Cardiovascular Disease Dataset
Description
This dataset was developed for scientific research aimed at analyzing and early detecting cardiovascular diseases. The dataset consists of a total of 2,025 objects (patient records), each of which is characterized by 70 clinical and laboratory signs. These indicators include demographic indicators of patients, anamnesis data, clinical symptoms, and laboratory test results. In the dataset, objects are designated by 22 classes (cases or diagnostic categories), which provides a convenient opportunity to solve multi-class classification problems. The characteristics within the dataset consist of various (numerical and categorical) data, reflecting the complexity of the actual clinical situation.
Files
Steps to reproduce
This Excel contains a total of 22 sheets. Each sheet represents a separate class. The row on each sheet corresponds to one patient, and each column corresponds to one of the 70 clinical symptoms or relevant variables collected through the questionnaire. The dataset can be used for classification, feature selection, statistical analysis, and comparative evaluation of machine learning models.