Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Here, the authors present a multinational study on the application of deep learning algorithms for COVID-19 diagnosis against multiple lung conditions as controls.

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Autores principales:	Stephanie A. Harmon, Thomas H. Sanford, Sheng Xu, Evrim B. Turkbey, Holger Roth, Ziyue Xu, Dong Yang, Andriy Myronenko, Victoria Anderson, Amel Amalou, Maxime Blain, Michael Kassin, Dilara Long, Nicole Varble, Stephanie M. Walker, Ulas Bagci, Anna Maria Ierardi, Elvira Stellato, Guido Giovanni Plensich, Giuseppe Franceschelli, Cristiano Girlando, Giovanni Irmici, Dominic Labella, Dima Hammoud, Ashkan Malayeri, Elizabeth Jones, Ronald M. Summers, Peter L. Choyke, Daguang Xu, Mona Flores, Kaku Tamura, Hirofumi Obinata, Hitoshi Mori, Francesca Patella, Maurizio Cariati, Gianpaolo Carrafiello, Peng An, Bradford J. Wood, Baris Turkbey
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/6f9c98cf760e4d96a63cb5040206bc04
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Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

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