ABSTRACT:
Cardiac arrhythmias are abnormal heart rhythms that can lead to serious health complications. Accurate and early prediction of arrhythmias can significantly improve patient outcomes. This research explores the development of a probabilistic model using machine learning techniques to predict cardiac arrhythmias based on electrocardiogram (ECG) data. The study aims to identify key predictors of arrhythmias and evaluate the effectiveness of various machine learning algorithms in making accurate predictions.
Cite this article:
Madiha Raza (2024), Probabilistic models for predicting cardiac arrhythmias using machine learning, Spectrum of Emerging Sciences, 4 (2) 2024, 11-16, 10.55878/SES2024-4-2-4, DOI: https://doi.org/10.55878/SES2024-4-2-4