Explainer: An interactive Agent for Explaining the Diagnosis of Cardiac Arrhythmia Generated by IK-DCBRC

Abstract

Interactions between medical applications and users involve a high level of trust, since many complex, automated applications are integrated and involve critical domains in which public health is paramount. Although uncertainty decreases the accuracy and trust of such medical applications under these circumstances, explanation-aware computing becomes crucial in improving the efficiency of these applications. This paper describes an intelligent agent that interacts with users to provide meaningful explanations of previous diagnoses supported by IK-DCBRC. The agent ensures intelligent interactions with users via a rule-based system that generates appropriate explanations according to the selected level of abstraction and the detected cardiac arrhythmia. The paper also describes a particular medical application, that is, cardiac arrhythmia with automatic diagnoses supported by the case-based reasoning classifier, IK-DCBRC.

The Vedic Design-Carry Look Ahead (VD-CLA): A Smart and Hardware-Friendly Implementation of the FIR Filter for ECG Signal Denoising

“…This described VD-CLA structure can improve by taking a gander at other electronic system performance metrics to seek the best arrangement of attributes intended for a specific denoising application, e.g., mean squared error (MSE), signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), bit error rate (BER), and [25,[36][37][38][39][40][41].…”