Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Mélissa Rollot"'
Autor:
Amanda Wilson, Alexandra Chiorean, Mario Aguiar, Davorka Sekulic, Patrick Pavlick, Neha Shah, Lisa Sniderman King, Marie Génin, Mélissa Rollot, Margot Blanchon, Simon Gosset, Martin Montmerle, Cliona Molony, Alexandra Dumitriu
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 18, Iss 1, Pp 1-13 (2023)
Abstract Background Early diagnosis of Gaucher disease (GD) allows for disease-specific treatment before significant symptoms arise, preventing/delaying onset of complications. Yet, many endure years-long diagnostic odysseys. We report the developmen
Externí odkaz:
https://doaj.org/article/cf3fc5e241db43cc80e829e8b825b578
Autor:
Juliana CN Chan, Jean Claude Mbanya, Jean‐Marc Chantelot, Marina Shestakova, Ambady Ramachandran, Hasan Ilkova, Lucille Deplante, Melissa Rollot, Lydie Melas‐Melt, Juan Jose Gagliardino, Pablo Aschner
Publikováno v:
Journal of Diabetes Investigation, Vol 15, Iss 9, Pp 1306-1316 (2024)
Abstract Aims/Introduction We analyzed patient‐reported outcomes of people with type 2 diabetes to better understand perceptions and experiences contributing to treatment adherence. Materials and Methods In the ongoing International Diabetes Manage
Externí odkaz:
https://doaj.org/article/5eefd2e4c63047268097de7fd18832ba
Autor:
Riccardo C. Bonadonna, Didac Mauricio, Dirk Mueller-Wieland, Mireille Bonnemaire, Nick Freemantle, Celine Mauquoi, Gregory Bigot, Alice Ciocca, Pierre Gourdy, Mélissa Rollot
Publikováno v:
BMJ Open
r-IGTP. Repositorio Institucional de Producción Científica del Instituto de Investigación Germans Trias i Pujol
instname
r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
r-IGTP. Repositorio Institucional de Producción Científica del Instituto de Investigación Germans Trias i Pujol
instname
r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
IntroductionType 2 diabetes mellitus (T2DM) is a common and heterogeneous disease. Using advanced analytic approaches to explore real-world data may identify different disease characteristics, responses to treatment and progression patterns. Insulin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3163f90404e3259a37f6bb1ba805a9d
https://fundanet.igtp.cat/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=5009
https://fundanet.igtp.cat/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=5009
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2023)
The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted populat
Externí odkaz:
https://doaj.org/article/a62d6552534d443cb8b280cc864d478f