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Assessment measures of an ensemble classifier based on the distributivity equation to predict the presence of severe coronary artery disease

Rak Ewa, Szczur Adam, Bazan Jan G., Bazan-Socha Stanisława

International Journal of Applied Mathematics and Computer Science

2023

Vol. 33, no. 3

361--377

The aim of this study is to apply and evaluate the usefulness of the hybrid classifier to predict the presence of serious coronary artery disease based on clinical data and 24-hour Holter ECG monitoring. Our approach relies on an ensemble classifier applying the distributivity equation aggregating base classifiers accordingly. Such a method may be helpful for physicians in the management of patients with coronary artery disease, in particular in the face of limited access to invasive diagnostic tests, i.e., coronary angiography, or in the case of contraindications to its performance. The paper includes results of experiments performed on medical data obtained from the Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland. The data set contains clinical data, data from Holter ECG (24-hour ECG monitoring), and coronary angiography. A leave-one-out cross-validation technique is used for the performance evaluation of the classifiers on a data set using the WEKA (Waikato Environment for Knowledge Analysis) tool. We present the results of comparing our hybrid algorithm created from aggregation with the distributive equation of selected classification algorithms (multilayer perceptron network, support vector machine, k-nearest neighbors, naïve Bayes, and random forests) with themselves on raw data.

The occurrence of arrhythmias and heart rate variability during diving in recreational divers using continuous electrocardiographic holter monitoring

Stelmaszczyk Łukasz, Starek-Stelmaszczyk Magdalena, Starek Maria, Kurek Łukasz, Żuchlińska-Kwiatkowska Joanna, Dębiński Michał

Polish Hyperbaric Research

2019

nr 4(69)

71--80

The aim of the research was to evaluate the occurrence of arrhythmias and heart rate variability during diving in recreational divers. Continuous electrocardiographic (ECG) Holter monitoring was conducted in a group of 50 divers (age 36,8 } 8,7). The recorded data included the duration of the dive, including a period of 60 minutes before the dive and 60 minutes after the dive. Moreover, divers filled in a questionnaire that had been prepared for the purpose of the study and the psychological tests State-Trait Anxiety Inventory (STAI). The ECG recordings were synchronised with dive computers to correlate the ECG changes with diving events and analysed for the heart rate, arrhythmias and conduction disorders. The average heart rate was the highest (M=107.34 beats/minute) before diving, and the lowest after diving (M = 102.00 beats/minute). Supraventricular arrhythmias were recorded in nineteen (38%) of the participants of the study. The number of arrhythmias during diving (M = 14,45) is significantly higher than before (M = 9,93, p < 0,01) and after dive (M = 6,02, p < 0,05). All results were obtained from the continuous ECG Holter monitoring. It seems that using continuous ECG monitoring in conditions similar to diving (physical and psychological stress), brings more benefits than traditional, resting electrocardiogram.