Comparison of two artificial intelligence-augmented ECG approaches: Machine learning and deep learning.

BACKGROUND: Artificial intelligence-augmented ECG (AI-ECG) refers to the application of novel AI solutions for complex ECG interpretation tasks. A broad variety of AI-ECG approaches exist, each having differing advantages and limitations relating to their creation and application. PURPOSE: To provide illustrative comparison of two general AI-ECG modeling approaches: machine learning (ML) and deep learning (DL). METHOD COMPARISON: Two AI-ECG algorithms were developed to carry out two separate tasks using ML and DL, respectively. ML modeling techniques were used to create algorithms designed for automatic wide QRS complex tachycardia differentiation into ventricular tachycardia and supraventricular tachycardia. A DL algorithm was formulated for the task of comprehensive 12­lead ECG interpretation. First, we describe the ML models for WCT differentiation, which rely upon expert domain knowledge to identify and formulate ECG features (e.g., percent monophasic time-voltage area [PMonoTVA]) that enable strong diagnostic performance. Second, we describe the DL method for comprehensive 12­lead ECG interpretation, which relies upon the independent recognition and analysis of a virtually incalculable number of ECG features from a vast collection of standard 12­lead ECGs. CONCLUSION: We have showcased two different AI-ECG methods, namely ML and DL respectively. In doing so, we highlighted the strengths and weaknesses of each approach. It is essential for investigators to understand these differences when attempting to create and apply novel AI-ECG solutions.

Wide complex tachycardia discrimination tool improves physicians' diagnostic accuracy.

BACKGROUND: Timely and accurate discrimination of wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular WCT (SWCT) is critically important. Previously we developed and validated an automated VT Prediction Model that provides a VT probability estimate using the paired WCT and baseline 12-lead ECGs. Whether this model improves physicians' diagnostic accuracy has not been evaluated. OBJECTIVE: We sought to determine whether the VT Prediction Model improves physicians' WCT differentiation accuracy. METHODS: Over four consecutive days, nine physicians independently interpreted fifty WCT ECGs (25 VTs and 25 SWCTs confirmed by electrophysiological study) as either VT or SWCT. Day 1 used the WCT ECG only, Day 2 used the WCT and baseline ECG, Day 3 used the WCT ECG and the VT Prediction Model's estimation of VT probability, and Day 4 used the WCT ECG, baseline ECG, and the VT Prediction Model's estimation of VT probability. RESULTS: Inclusion of the VT Prediction Model data increased diagnostic accuracy versus the WCT ECG alone (Day 3: 84.2% vs. Day 1: 68.7%, p 0.009) and WCT and baseline ECGs together (Day 3: 84.2% vs. Day 2: 76.4%, p 0.003). There was no further improvement of accuracy with addition of the baseline ECG comparison to the VT Prediction Model (Day 3: 84.2% vs. Day 4: 84.0%, p 0.928). Overall sensitivity (Day 3: 78.2% vs. Day 1: 67.6%, p 0.005) and specificity (Day 3: 90.2% vs. Day 1: 69.8%, p 0.016) for VT were superior after the addition of the VT Prediction Model. CONCLUSION: The VT Prediction Model improves physician ECG diagnostic accuracy for discriminating WCTs.

Taquicardia de complejos anchos. un ejercicio académico / Tachycardia of wide complexes. an academic year

Las taquicardias de complejos anchos (TCA) constituyen un problema diagnóstico de importancia, tanto para el médico general como para el especialista en el área, debido a que pueden corresponder a patologías cuyo origen puede ser supraventricular o ventricular. El diagnóstico acertado del tipo de arritmia responsable de esta taquicardia es de vital importancia tanto desde el punto de vista terapéutico como de pronóstico. Un esquema de tratamiento inadecuado basado en un diagnóstico errado, no solamente no corregirá el problema sino que también puede empeorar la situación clínica del paciente incluso llevándolo a su muerte. En el presente artículo se muestra un caso típico de TCA, se interroga el diagnóstico correcto y el tratamiento ideal que debe recibir; además, se hace una revisión del tema resaltando las bases para el adecuado diagnóstico electrocardiográfico.

The wide complex tachycardias are a difficult diagnosis and they are important for the general doctor and the specialist too because they can origin in different level like supraventricular and ventricular. The correct diagnosis of the kind of arrhythmia that produces the wide complex tachycardia is very important for the therapeutic and prognosis of the patients. A bad schedule of treatment in relation with a bad diagnosis won’t fi x the clinical problem and it can produce death of the patient. This article shows a typical case of Wide complex tachycardias and ask questions in relation with diagnosis and treatment of this disease. It reviews the electrocardiography diagnosis too.