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Simulating federated learning for steatosis detection using ultrasound images

Author(s): Qi Y; Vianna P; Cadrin-Chênevert A; Blanchet K; Montagnon E; Belilovsky E; Wolf G; Mullie LA; Cloutier G; Chassé M; Tang A;

We aimed to implement four data partitioning strategies evaluated with four federated learning (FL) algorithms and investigate the impact of data distribution on FL model performance in detecting steatosis using B-mode US images. A private dataset (153 patients; 1530 images) and a public dataset ...

Article GUID: 38858500


Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis

Author(s): Vianna P; Calce SI; Boustros P; Larocque-Rigney C; Patry-Beaudoin L; Luo YH; Aslan E; Marinos J; Alamri TM; Vu KN; Murphy-Lavallée J; Billiard JS; Montagnon E; Li H; Kadoury S; Nguyen BN; Gauthier S; Therien B; Rish I; Belilovsky E; Wolf ...

Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepatic steatosis in NAFLD at US, with biopsy as the ...

Article GUID: 37787678


Monitoring the evolution of individuals' flood-related adaptive behaviors over time: two cross-sectional surveys conducted in the Province of Quebec, Canada.

Author(s): Valois P; Tessier M; Bouchard D; Talbot D; Morin AJS; Anctil F; Cloutier G;

Climate change is predicted to increase the frequency and intensity of floods in the province of Quebec, Canada. Therefore, in 2015, to better monitor the level of adaptation to flooding of Quebec residents living in or near a flood-prone area, the Quebec Observatory of Adaptation to Climate Change developed five indices of adaptation to flooding, accordi ...

Article GUID: 33143677


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