The integration of Deep Learning (DL) into medical diagnostics has shown remarkable potential, yet the "black-box" nature of these models remains a significant barrier to clinical adoption. Physicians require not only accurate predictions but also a comprehensible rationale behind algorithmic decisions. This paper proposes a novel framework, ECG-Net-X, designed to classify cardiac arrhythmias from Electrocardiogram (ECG) signals while providing human-interpretable explanations. By combining Convolutional Neural Networks (CNNs) for feature extraction with attention-based mechanisms for localization, our model highlights specific regions of the ECG signal influencing the classification decision. We evaluate ECG-Net-X on the MIT-BIH Arrhythmia Database, achieving a classification accuracy of 98.4%. Furthermore, qualitative evaluation by cardiologists confirms that the attention maps align with known physiological biomarkers. This study bridges the gap between high-performance AI algorithms and the explainability required for trustworthy clinical application.
Keywords: Explainable AI (XAI), ECG Classification, Deep Learning, Cardiology, Healthcare Informatics. soumya nandana krishnan
No artistic journey is without its valleys. Soumya faced significant backlash early in her career when she rejected a high-profile commercial film because the script required her to perform a "skin show" that she felt was gratuitous. The industry labeled her "difficult to work with." For nearly 18 months, offers dried up. The integration of Deep Learning (DL) into medical
However, the tide turned when the #MeToo movement and the rise of women-centric cinema changed the industry's dynamics. Producers began looking for actors with integrity and audience trust. Soumya Nandana Krishnan, who had spent her hiatus doing street plays and voice-over for documentaries, was suddenly in demand again. Her comeback film, "The Fourth Wall," won the state award for Best Actress. No artistic journey is without its valleys
Soumya Nandana Krishnan has established herself as a versatile writer, straddling the realms of fiction and verse. Her notable achievements include: