In recent years, heart disease has remained the leading cause of death worldwide, including in Indonesia. Among various heart conditions, myocardial infarction (MI) is one of the most common forms of coronary heart disease. Early detection of MI is crucial to prevent more severe complications, including sudden death. One effective method for detecting myocardial infarction is through the analysis of electrocardiogram (EKG) signals.
The integration of artificial intelligence (AI) technology has significantly advanced the classification of heart diseases based on EKG signals. However, the interpretability of the decision-making results from machine learning models is essential to ensure clinical trust and validity. This research, conducted by Farhatul Fityah, aims to evaluate the interpretability of a simple rule-based machine learning model in the qualitative classification of myocardial infarction by cardiologists.
Farhatul Fityah atau yang akrab disaba Tya adalah Mahasiwa Magister Teknik Biomedis untuk menyusun menjadi sebuah tesis yang bejudul Evaluasi Interpretabilitas Rule-Based Classifier dalam Klasifikasi Myocardial Infarction Berdasarkan Fitur Sintaksis Sinyal EKG, dan berhasil lulus dengan predikat cumlaude pada 31 januari 2025
