Author: Guillaume Chassagnon; Maria Vakalopoulou; Enzo Battistella; Stergios Christodoulidis; Trieu-Nghi Hoang-Thi; Severine Dangeard; Eric Deutsch; Fabrice Andre; Enora Guillo; Nara Halm; Stefany El Hajj; Florian Bompard; Sophie Neveu; Chahinez Hani; Ines Saab; Alienor Campredon; Hasmik Koulakian; Souhail Bennani; Gael Freche; Aurelien Lombard; Laure Fournier; Hippolyte Monnier; Teodor Grand; Jules Gregory; Antoine Khalil; Elyas Mahdjoub; Pierre-Yves Brillet; Stephane Tran Ba; Valerie Bousson; Marie-Pierre Revel; Nikos Paragios
Title: AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia Document date: 2020_4_22
ID: nxm1jr0x_35
Snippet: CT parameters between the 6 centers were compared using the analysis of variance, while patient characteristics between training/validation and test datasets were compared using chi-square and Student's t-tests......
Document: CT parameters between the 6 centers were compared using the analysis of variance, while patient characteristics between training/validation and test datasets were compared using chi-square and Student's t-tests.
Search related documents:
Co phrase search for related documents- test dataset and training validation: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
- test dataset training validation and training validation: 1, 2, 3, 4, 5, 6
Co phrase search for related documents, hyperlinks ordered by date