Interpretable arrhythmia detection in ECG scans using deep learning ensembles: a genetic programming approach
A deep learning ensemble framework for detecting cardiac arrhythmias and predicting atrial fibrillation recurrence from ECG scans.
Data Scientist & Machine Learning Researcher
I’m a PhD candidate in Computer Science at the Silesian University of Technology, specializing in machine learning applications in medicine. My research focuses on developing deep learning solutions for medical imaging and clinical decision support systems, with emphasis on interpretability and real-world clinical utility.
A deep learning ensemble framework for detecting cardiac arrhythmias and predicting atrial fibrillation recurrence from ECG scans.
A genetic programming algorithm for building deep learning ensembles for ECG arrhythmia classification.
A deep learning approach for automated hepatocellular carcinoma analysis in multi-phase CT scans.