Lessmann, Nikolas ;
Sanchez, Clara ;
Beenen, Ludo...
Lessmann , N , Sanchez , C , Beenen , L , Boulogne , L H , Brink , M , Calli , E , Charbonnier , J-P , Dofferhoff , T , van Everdingen , W M , Gerke , P K , Geurts , B , Gietema , H A , Groeneveld , M , van Harten , L , Hendrix , N , Hendrix , W , Huisman , H J , Isgum , I , Jacobs , C , Kluge , R , Kok , M , Krdzalic , J , Lassen-Schmidt , B , van Leeuwen , K , Meakin , J , Overkamp , M , Vellinga , T V R , van Rikxoort , E M , Samperna , R , Schaefer-Prokop , C , Schalekamp , S , Scholten , E T , Sital , C , Stoeger , J L , Teuwen , J , Venkadesh , K V , de Vente , C , Vermaat , M , Xie , W , de Wilde , B , Prokop , M & van Ginneken , B 2021 , ' Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence ' , Radiology , vol. 298 , no. 1 , pp. E18-E28 . https://doi.org/10.1148/radiol.2020202439.
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2021
