Akyea, Ralph Kwame; Figliozzi, Stefano; Lopes, Pedro M.; Bauer, Klemens B.; Moura-Ferreira, Sara; Tondi, Lara; Mushtaq, Saima; Censi, Stefano; Pavon, Anna Giulia; Bassi, Ilaria; Galian-Gay, Laura; Teske, Arco J.; Biondi, Federico; Filomena, Domenico; Stylianidis, Vasileios; Torlasco, Camilla; Muraru, Denisa; Monney, Pierre; Quattrocchi, Giuseppina; Maestrini, Viviana; Agati, Luciano; Monti, Lorenzo; Pedrotti, Patrizia; Vandenberk, Bert; Squeri, Angelo; Lombardi, Massimo; Ferreira, Antonio M.; Schwitter, Juerg; Aquaro, Giovanni Donato; Pontone, Gianluca; Chiribiri, Amedeo; Palomares, José F.Rodríguez; Yilmaz, Ali; Andreini, Daniele; Florian, Anca Rezeda; Francone, Marco; Leiner, Tim; Abecasis, João; Badano, Luigi Paolo; Bogaert, Jan; Georgiopoulos, Georgios; Masci, Pier Giorgio
(Radiological Society of North America Inc., 2024-06)
Purpose: To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials and Methods: This retrospective study included patients with MVP without ...