no code implementations • 5 Mar 2024 • Samuel I. Berchuck, Felipe A. Medeiros, Sayan Mukherjee, Andrea Agazzi
The generalized linear mixed model (GLMM) is a popular statistical approach for handling correlated data, and is used extensively in applications areas where big data is common, including biomedical data settings.
no code implementations • 4 Oct 2021 • Sayan Mandal, Alessandro A. Jammal, Felipe A. Medeiros
One of the leading causes of blindness is glaucoma, which is challenging to detect since it remains asymptomatic until the symptoms are severe.
no code implementations • 15 Oct 2020 • Shounak Datta, Eduardo B. Mariottoni, David Dov, Alessandro A. Jammal, Lawrence Carin, Felipe A. Medeiros
Due to the SAP test's innate difficulty and its high test-retest variability, we propose the RetiNerveNet, a deep convolutional recursive neural network for obtaining estimates of the SAP visual field.
1 code implementation • 24 Aug 2019 • Samuel I. Berchuck, Felipe A. Medeiros, Sayan Mukherjee
As big spatial data becomes increasingly prevalent, classical spatiotemporal (ST) methods often do not scale well.
no code implementations • 21 Dec 2018 • Sonia Phene, R. Carter Dunn, Naama Hammel, Yun Liu, Jonathan Krause, Naho Kitade, Mike Schaekermann, Rory Sayres, Derek J. Wu, Ashish Bora, Christopher Semturs, Anita Misra, Abigail E. Huang, Arielle Spitze, Felipe A. Medeiros, April Y. Maa, Monica Gandhi, Greg S. Corrado, Lily Peng, Dale R. Webster
An algorithm trained on fundus images alone can detect referable GON with higher sensitivity than and comparable specificity to eye care providers.
no code implementations • 20 Oct 2018 • Felipe A. Medeiros, Alessandro A. Jammal, Atalie C. Thompson
The mean prediction of average RNFL thickness from all 6, 292 optic disc photos in the test set was 83. 3$\pm$14. 5 $\mu$m, whereas the mean average RNFL thickness from all corresponding SDOCT scans was 82. 5$\pm$16. 8 $\mu$m (P = 0. 164).