AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia
Guillaume Chassagnon, Maria Vakalopoulou, Enzo Battistella, Stergios Christodoulidis, Trieu-Nghi Hoang-Thi, Séverine Dangeard, Éric Deutsch, Fabrice André, Enora Guillo, Nara Halm, Stefany El Hajj, Florian Bompard, Sophie Neveü, Chahinez Hani, Inès Saab, Aliénor Campredon, Hasmik Koulakian, Souhail Bennani, Gaël Freche, Maxime Barat, Aurélien Lombard, Laure Fournier, Hippolyte Monnier, Téodor Grand, Jules Grégory, Yann Nguyen, Antoine Khalil, Elyas Mahdjoub, Pierre‐Yves Brillet, Stéphane Tran Ba, Valérie Bousson, Ahmed Mekki, Robert-Yves Carlier, Marie‐Pierre Revel, Nikos Paragios
Topics & Concepts
Outcome (game theory)Artificial intelligenceCoronavirus disease 2019 (COVID-19)Intensive care unitMachine learningPneumoniaMedical physicsMedical imagingMedicineComputer scienceDiseaseIntensive care medicineInfectious disease (medical specialty)PathologyInternal medicineMathematicsMathematical economicsCOVID-19 diagnosis using AIRadiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education