2 citations · 4 across the 4 of their papers we have counts for
4 papers
Learning a binary search with a recurrent neural network. A novel approach to ordinal regression analysis
Louis Falissard, Karim Bounebache, Grégoire Rey
Deep neural networks are a family of computational models that are naturally suited to the analysis of hierarchical data such as, for instance, sequential data with the use of recu…
Neural translation and automated recognition of ICD10 medical entities from natural language
Louis Falissard, Claire Morgand, Sylvie Roussel +4
The recognition of medical entities from natural language is an ubiquitous problem in the medical field, with applications ranging from medical act coding to the analysis of electr…
A deep artificial neural network based model for underlying cause of death prediction from death certificates
Louis Falissard, Claire Morgand, Sylvie Roussel +4
Underlying cause of death coding from death certificates is a process that is nowadays undertaken mostly by humans with a potential assistance from expert systems such as the Iris…
An empirical comparative study of approximate methods for binary graphical models; application to the search of associations among causes of death in French death certificates
Vivian Viallon, Onureena Banerjee, Gregoire Rey +2
Looking for associations among multiple variables is a topical issue in statistics due to the increasing amount of data encountered in biology, medicine and many other domains invo…