Adil Salihu, David Meier, Nathalie Noirclerc, Ioannis Skalidis, Sarah Mauler-Wittwer, Frederique Recordon, Matthias Kirsch, Christan Roguelov, Alexandre Berger, Xiaowu Sun, Emmanuel Abbe, Carlo Marcucci, Valentina Rancati, Lorenzo Rosner, Emanuelle Scala, David C Rotzinger, Marc Humbert, Olivier Muller, Henri Lu, Stephane Fournier
BACKGROUND: Multidisciplinary Heart Teams (HTs) play a central role in the management of valvular heart diseases. However, the comprehensive evaluation of patients' data can be hindered by logistical challenges, which in turn may affect the care they receive. AIMS: This study aimed to explore the ability of artificial intelligence (AI), particularly large language models (LLMs), to improve clinical decision-making and enhance the efficiency of HTs. METHODS: Data from patients with severe aortic stenosis presented at HT meetings were retrospectively analysed...
April 15, 2024: EuroIntervention