Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Jérôme Azé"'
Autor:
Gwenolé Quellec, Sofian Berrouiguet, Margot Morgiève, Jonathan Dubois, Marion Leboyer, Guillaume Vaiva, Jérôme Azé, Philippe Courtet
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Over 700,000 people die by suicide annually. Collecting longitudinal fine-grained data about at-risk individuals, as they occur in the real world, can enhance our understanding of the temporal dynamics of suicide risk, leading to better iden
Externí odkaz:
https://doaj.org/article/be6323e012ea4122a69b9c23ba1bf687
Autor:
Margot Morgiève, Daniel Yasri, Catherine Genty, Jonathan Dubois, Marion Leboyer, Guillaume Vaiva, Sofian Berrouiguet, Jérôme Azé, Philippe Courtet
Publikováno v:
Frontiers in Psychiatry, Vol 13 (2022)
BackgroundAs mHealth may contribute to suicide prevention, we developed emma, an application using Ecological Momentary Assessment and Intervention (EMA/EMI).ObjectiveThis study evaluated emma usage rate and acceptability during the first month and s
Externí odkaz:
https://doaj.org/article/6efe902590b64b27af6bc6cf96702c53
Publikováno v:
PLoS ONE, Vol 14, Iss 5, p e0215649 (2019)
BackgroundCurrently, cardiovascular disease (CVD) is widely acknowledged to be the first leading cause of fatality in the world with 31% of all deaths worldwide and is predicted to remain as such in 2030. Furthermore, CVD is also a major cause of mor
Externí odkaz:
https://doaj.org/article/f9d8b76fe6fa4d7b9e0e1bd176fc73b4
Autor:
Jérôme Azé, Christophe Sola, Jian Zhang, Florian Lafosse-Marin, Memona Yasmin, Rubina Siddiqui, Kristin Kremer, Dick van Soolingen, Guislaine Refrégier
Publikováno v:
PLoS ONE, Vol 10, Iss 7, p e0130912 (2015)
Infra-species taxonomy is a prerequisite to compare features such as virulence in different pathogen lineages. Mycobacterium tuberculosis complex taxonomy has rapidly evolved in the last 20 years through intensive clinical isolation, advances in sequ
Externí odkaz:
https://doaj.org/article/5ea71171f0174272879569a7aa65ab50
Publikováno v:
PLoS ONE, Vol 9, Iss 9, p e108928 (2014)
Protein-RNA complexes provide a wide range of essential functions in the cell. Their atomic experimental structure solving, despite essential to the understanding of these functions, is often difficult and expensive. Docking approaches that have been
Externí odkaz:
https://doaj.org/article/3abb68da459f471396e53343b264fd47
Autor:
Damien M de Vienne, Jérôme Azé
Publikováno v:
PLoS ONE, Vol 7, Iss 11, p e48728 (2012)
The prediction of the network of protein-protein interactions (PPI) of an organism is crucial for the understanding of biological processes and for the development of new drugs. Machine learning methods have been successfully applied to the predictio
Externí odkaz:
https://doaj.org/article/13f13cf2e7ea4abf83ddd08f9a55a98e
Publikováno v:
PLoS ONE, Vol 6, Iss 4, p e18541 (2011)
A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to
Externí odkaz:
https://doaj.org/article/d795b15b2572438a8918c5e5870858dc
Publikováno v:
World Wide Web. 26:799-825
Autor:
Hugo Le Baher, Jérôme Azé, Sandra Bringay, Pascal Poncelet, Nancy Rodriguez, Caroline Dunoyer
Publikováno v:
Caring is Sharing – Exploiting the Value in Data for Health and Innovation ISBN: 9781643683881
Machine learning methods are becoming increasingly popular to anticipate critical risks in patients under surveillance reducing the burden on caregivers. In this paper, we propose an original modeling that benefits of recent developments in Graph Con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::823f617564e0bc614947e83f2407c91b
https://doi.org/10.3233/shti230205
https://doi.org/10.3233/shti230205
Autor:
Leonardo Moros, Jérôme Azé, Sandra Bringay, Pascal Poncelet, Maximilien Servajean, Caroline Dunoyer
Publikováno v:
Caring is Sharing – Exploiting the Value in Data for Health and Innovation ISBN: 9781643683881
Context: We present a post-hoc approach to improve the recall of ICD classification. Method: The proposed method can use any classifier as a backbone and aims to calibrate the number of codes returned per document. We test our approach on a new strat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fd89f0d271fd6dd696e5ec16b324b54
https://doi.org/10.3233/shti230264
https://doi.org/10.3233/shti230264