Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Dominique Mercier"'
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
Since the advent of deep learning (DL), the field has witnessed a continuous stream of innovations. However, the translation of these advancements into practical applications has not kept pace, particularly in safety-critical domains where artificial
Externí odkaz:
https://doaj.org/article/0992a27ebbfa4334bd6d541566773410
Autor:
Gregor Duwe, Dominique Mercier, Crispin Wiesmann, Verena Kauth, Kerstin Moench, Markus Junker, Christopher C. M. Neumann, Axel Haferkamp, Andreas Dengel, Thomas Höfner
Publikováno v:
Cancer Medicine, Vol 13, Iss 12, Pp n/a-n/a (2024)
Abstract Artificial intelligence (AI) promises to be the next revolutionary step in modern society. Yet, its role in all fields of industry and science need to be determined. One very promising field is represented by AI‐based decision‐making too
Externí odkaz:
https://doaj.org/article/62ca11f1d50c468f8bedcc1baa472402
Autor:
Jacques Pépin, France Desjardins, Alex Carignan, Michel Lambert, Isabelle Vaillancourt, Christiane Labrie, Dominique Mercier, Rachel Bourque, Louiselle LeBlanc
Publikováno v:
PLoS ONE, Vol 17, Iss 5, p e0267781 (2022)
IntroductionThe identification and treatment of latent tuberculosis infection (LTBI) among immigrants from high-incidence regions who move to low-incidence countries is generally considered an ineffective strategy because only ≈14% of them comply w
Externí odkaz:
https://doaj.org/article/5804abacfe8a41ecab1bfd34fbce5d41
Publikováno v:
IEEE Access, Vol 7, Pp 67027-67040 (2019)
This paper presents a novel framework for the demystification of convolutional deep learning models for time-series analysis. This is a step toward making informed/explainable decisions in the domain of time series, powered by deep learning. There ha
Externí odkaz:
https://doaj.org/article/beea0a829f724a28b8f2c2037b48b4c3
Publikováno v:
Sensors, Vol 22, Iss 11, p 4084 (2022)
Deep neural networks are one of the most successful classifiers across different domains. However, their use is limited in safety-critical areas due to their limitations concerning interpretability. The research field of explainable artificial intell
Externí odkaz:
https://doaj.org/article/9a1e52f4514a49029872a28540304ec2
Publikováno v:
Sensors, Vol 21, Iss 21, p 7373 (2021)
With the rise in the employment of deep learning methods in safety-critical scenarios, interpretability is more essential than ever before. Although many different directions regarding interpretability have been explored for visual modalities, time s
Externí odkaz:
https://doaj.org/article/881a494110f14e32aac9ec0578d41da6
Autor:
Jamila El-Bchiri, Agathe Guilloux, Peggy Dartigues, Etienne Loire, Dominique Mercier, Olivier Buhard, Iradj Sobhani, Pierre de la Grange, Didier Auboeuf, Françoise Praz, Jean-François Fléjou, Alex Duval
Publikováno v:
PLoS ONE, Vol 3, Iss 7, p e2583 (2008)
Nonsense-mediated mRNA Decay (NMD) degrades mutant mRNAs containing premature termination codon (PTC-mRNAs). Here we evaluate the consequence of NMD activity in colorectal cancers (CRCs) showing microsatellite instability (MSI) whose progression is a
Externí odkaz:
https://doaj.org/article/607ada48a4f2439185949986fcb32e93
Publikováno v:
Néphrologie & Thérapeutique. 18:534-540
This paper presents a comprehensive benchmarking of privacy preserving techniques for document image classification.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f6a32a6ccf20a8dd71efc75e1b24f1c
https://doi.org/10.36227/techrxiv.19518925
https://doi.org/10.36227/techrxiv.19518925
Publikováno v:
Nephrologietherapeutique. 18(6)
The possibility of indirect linkage between data from the French REIN registry and data from the National Health Data System makes it possible to enhance knowledge of the care pathway of patients with severe kidney disease. Taking an interest in hosp