Litcius/Paper detail

Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets

Fabrizio D’Ascenzo, Ovidio De Filippo, Guglielmo Gallone, Gianluca Mittone, Marco A. Deriu, Mario Iannaccone, Albert Ariza‐Solé, Christoph Liebetrau, Sergio Manzano‐Fernández, Giorgio Quadri, Tim Kinnaird, Gianluca Campo, José P.S. Henriques, James M. Hughes, Alberto Domínguez‐Rodríguez, Marco Aldinucci, Umberto Morbiducci, Giuseppe Patti, Sergio Raposeiras‐Roubín, Emad Abu‐Assi, Gaetano Maria De Ferrari, Francesco Piroli, Andrea Saglietto, Federico Conrotto, Pierluigi Omedè, Antonio Montefusco, Mauro Pennone, Francesco Bruno, Pier Paolo Bocchino, Giacomo Boccuzzi, Enrico Cerrato, Ferdinando Varbella, Michela Sperti, Stephen B. Wilton, Lazar Velicki, Ioanna Xanthopoulou, Ángel Cequier, Andrés Íñiguez, Isabel Muñoz Pousa, M Cespon Fernandez, Berenice Caneiro Queija, Rafael Cobas Paz, Ángel López‐Cuenca, Alberto Garay, Pedro Flores Blanco, Andrea Rognoni, Giuseppe Biondi‐Zoccai, Simone Biscaglia, Iván J. Núñez‐Gil, Toshiharu Fujii, Alessandro Durante, Xiantao Song, Tetsuma Kawaji, Dimitrios Alexopoulos, Zenon Huczek, José Ramón González‐Juanatey, Shaoping Nie, Masa‐aki Kawashiri, Iacopo Colonnelli, Barbara Cantalupo, Roberto Esposito, Sergio Leonardi, Walter Grosso Marra, Alaide Chieffo, Umberto Michelucci, Dario Piga, Marta Malavolta, Sebastiano Gili, Marco Mennuni, Claudio Montalto, Luigi Oltrona Visconti, Yasir Arfat

2021The Lancet335 citationsDOIOpen Access PDF

Topics & Concepts

MedicineCohortAcute coronary syndromeMyocardial infarctionReceiver operating characteristicInternal medicineArea under the curveCohort studyProspective cohort studyMachine learningComputer scienceAcute Myocardial Infarction ResearchSepsis Diagnosis and TreatmentMachine Learning in Healthcare