A myocardial infarction (MI), commonly known as a heart attack, occurs when blood flow decreases or stops to a part of the heart, causing damage to the heart muscle. The most common symptom is chest pain or discomfort which may travel into the shoulder, arm, back, neck or jaw.Often it occurs in the center or left side of the chest and lasts for more than a few minutes.The discomfort may occasionally feel like heartburn. Other symptoms may include shortness of breath, nausea, feeling faint, a cold sweat or feeling tired. About 30% of people have atypical symptoms. Women more often present without chest pain and instead have neck pain, arm pain or feel tired. Among those over 75 years old, about 5% have had an MI with little or no history of symptoms. An MI may cause heart failure, an irregular heartbeat, cardiogenic shock or cardiac arrest.
Problems of real-life complexity are needed to test and compare various data mining and pattern recognition methods. The proposed database can be used to solve two practically important problems: predicting complications of Myocardial Infarction (MI) based on information about the patient (i) at the time of admission and (ii) on the third day of the hospital period. Another important group of tasks is phenotyping of disease (cluster analysis), dynamic phenotyping (filament extraction and identification of disease trajectories) and visualization (disease mapping).
Source : https://doi.org/10.25392/leicester.data.12045261.v3