Detecting Paroxysmal Atrial Fibrillation From an Electrocardiogram in Sinus Rhythm: External Validation of the AI Approach.

Background: Atrial fibrillation (AF) may occur asymptomatically and can be diagnosed only with electrocardiography (ECG) while the arrhythmia is present.

Objectives: The aim of this study was to independently validate the approach of using artificial intelligence (AI) to identify underlying paroxysmal AF from a 12-lead ECG in sinus rhythm (SR).

Methods: An AI algorithm was trained to identify patients with underlying paroxysmal AF, using electrocardiographic data from all in- and outpatients from a single center with at least 1 ECG in SR.

Comparison of SARS-CoV-2 Antibody Response Following Vaccination With BNT162b2 and mRNA-1273.

This study compares the immune responses to the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) COVID-19 vaccines in health care workers in Belgium.

LISA, the next generation: from a web-based application to a fat client.

The LISA application, developed by the University Hospitals Leuven, permits referring physicians to consult the electronic medical records of their patients over the internet in a highly secure way. We decided to completely change the way we secured the application, discard the existing web application and build a completely new application, based on the in-house developed hospital information system, used in the University Hospitals Leuven. The result is a fat Java client, running on a Windows Terminal Server, secured by a commercial SSL-VPN solution.