Robust Artificial Intelligence Tool for Atrial Fibrillation Diagnosis: Novel Development Approach Incorporating Both Atrial Electrograms and Surface ECG and Evaluation by Head-to-Head Comparison With Hospital-Based Physician ECG Readers.

Background: Atrial fibrillation (AF) increases risk of embolic stroke, and in postoperative patients, increases cost of care. Consequently, ECG screening for AF in high-risk patients is important but labor-intensive. Artificial intelligence (AI) may reduce AF detection workload, but AI development presents challenges.

Ambulatory ECG monitoring for syncope and collapse in United States, Europe, and Japan: The patients' viewpoint.

Background: Practice guidelines provide clinicians direction for the selection of ambulatory ECG (AECG) monitors in the evaluation of syncope/collapse. However, whether patients' understand differences among AECG systems is unknown.

Methods And Results: A survey was conducted of USA (n = 99), United Kingdom (UK)/Germany (D) (n = 75) and Japan (n = 40) syncope/collapse patients who underwent diagnostic AECG monitoring.