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_27
Snippet: where α is a constant, ||w|| 1 is the L1-norm of the coefficient vector and n is the number of samples. The Lasso method was used with 200 alphas along a regularization path of length 0.01 and limited to 1000 iterations. The staging/prognosis component was addressed using an ensemble learning approach. First, the training data set was subdivided into training and validation set on the principle of 80% − 20% while respecting that the distributi.....
Document: where α is a constant, ||w|| 1 is the L1-norm of the coefficient vector and n is the number of samples. The Lasso method was used with 200 alphas along a regularization path of length 0.01 and limited to 1000 iterations. The staging/prognosis component was addressed using an ensemble learning approach. First, the training data set was subdivided into training and validation set on the principle of 80% − 20% while respecting that the distribution of classes between the two subsets was identical to the observed one. We have created 10 subdivisions on this basis and evaluated the average performance of the following supervised classification methods: These features included first order features (maximum attenuation, skewness and 90th percentile), shape features (surface, maximum 2D diameter per slice and volume) and texture features (non-uniformity of the GLSZM and GLRLM).
Search related documents:
Co phrase search for related documents- classification method and shape feature: 1
- classification method and staging prognosis: 1
- ensemble learning approach and learning approach: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
- Lasso method and learning approach: 1, 2
- learning approach and sample number: 1
- learning approach and shape feature: 1
- order feature and shape feature: 1
Co phrase search for related documents, hyperlinks ordered by date