31 citations · 195 across the 31 of their papers we have counts for
4 papers · 1 filter
Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach
Sebastiano Barbieri, Suneela Mehta, Billy Wu +4
AIMS. This study compared the performance of deep learning extensions of survival analysis models with traditional Cox proportional hazards (CPH) models for deriving cardiovascular…
A characterization of Sturmian sequences by indistinguishable asymptotic pairs
Sebastián Barbieri, Sébastien Labbé, Štěpán Starosta
We give a new characterization of biinfinite Sturmian sequences in terms of indistinguishable asymptotic pairs. Two asymptotic sequences on a full -shift are indistingu…
Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients
Misha P. T. Kaandorp, Sebastiano Barbieri, Remy Klaassen +5
: Earlier work showed that IVIM-NET, an unsupervised physics-informed deep neural network, was more accurate than other state-of-the-art intravoxel-incohere…
Gibbsian representations of continuous specifications: the theorems of Kozlov and Sullivan revisited
Sebastián Barbieri, Ricardo Gómez, Brian Marcus +2
The theorems of Kozlov and Sullivan characterize Gibbs measures as measures with positive continuous specifications. More precisely, Kozlov showed that every positive continuous sp…