COVID-19 pneumonia accurately detected on chest radiographs with artificial intelligence

Autor: Francisco Dorr, Hernán Chaves, María Mercedes Serra, Andrés Ramirez, Martín Elías Costa, Joaquín Seia, Claudia Cejas, Marcelo Castro, Eduardo Eyheremendy, Diego Fernández Slezak, Mauricio F. Farez, Marcelo Villalobos Olave, David Herquiñigo Reckmann, Christian Pérez, Jairo Hernández Pinzon, Omar García Almendro, David Valdez, Romina Julieta Montoya, Emilia Osa Sanz, Nadia Ivanna Stefanoff, Andres Hualpa, Milagros Di Cecco, Harol Sotelo, Federico Ferreyra Luaces, Francisco Larzabal, Julian Ramirez Acosta, Rodrigo José Mosquera Luna, Vicente Castro, Flavia Avallay, Saul Vargas, Sergio Villena, Rosario Forlenza, Joaquin Martinez Pereira, Macarena Aloisi, Manuel Conde Blanco, Federico Diaz Telli, Maria Sol Toronchik, Claudio Gutierrez Occhiuzzi, Gisella Fourzans, Pablo Kuschner, Rosa Castagna, Bibiana Abaz, Daniel Casero, María Saborido, Marcelano Escolar, Carlos Lineros, Silvina De Luca, Graciela Doctorovich, Laura Dragonetti, Cecilia Carrera, Juan Costa Cañizares, Leandro Minuet, Victor Charcopa, Carlos Mamani, Adriana Toledo, María Julieta Vargas, Angela Quiroz, Eros Angeletti, Jessica Goyo Pinto, Christian Correa, José Pizzorno, Rita De Luca, Jose Rivas, Marisa Concheso, Alicia Villareal, Mayra Zuleta, Guido Barmaimon

Publikováno v: Intelligence-Based Medicine
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET

Purpose To investigate the diagnostic performance of an Artificial Intelligence (AI) system for detection of COVID-19 in chest radiographs (CXR), and compare results to those of physicians working alone, or with AI support. Materials and methods An A

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0729c850582b3243fc333066375c8cbf
http://europepmc.org/articles/PMC7674009