Publicaciones

Affichage de 1221 à 1230 sur 5525


  • ART

A snapshot of the Covid-19 pandemic among pregnant women in France

Gilles Kayem, Florence Bretelle, Thomas Schmitz, Vivien Alessandrini, Elie Azria, Julie Blanc, Caroline Bohec, Marie Bornes, Pierre-François Ceccaldi, Yasmine Chalet, Céline Chauleur, Anne-Gael Cordier, Philippe Deruelle, Raoul Desbriere, Muriel Doret, Michel Dreyfus, Marine Driessen, Marion Fermaut, Denis Gallot, Charles Garabedian, Cyril Huissoud, Edouard E. Lecarpentier, Dominique Luton, Olivier Morel, Franck Perrotin, Olivier Picone, Patrick Rozenberg, Loïc Sentilhes, Jeremy Sroussi, Christophe Vayssiere, Eric Verspyck, Alexandre Vivanti, Norbert Winer

Objective To describe the course over time of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in French women from the beginning of the pandemic until mid-April, the risk profile of women with respiratory complications, and short-term pregnancy outcomes. Methods We collected...

Journal of Gynecology Obstetrics and Human Reproduction, 2020, 49 (7), pp.101826. ⟨10.1016/j.jogoh.2020.101826⟩. ⟨hal-02869022⟩

  • COMM

Simultaneous Estimation of State and Unknown Input for TS Fuzzy Systems with Unmeasured Premise Variables

Jun-Tao Pan, Tran Anh-Tu Nguyen, Thierry-Marie Guerra, Jimmy Lauber, Weiwei Zhang

Designing unknown input (UI) observers for Takagi-Sugeno (TS) fuzzy systems is known as a challenging issue, especially when the premise variables are unmeasured. This paper presents a new approach to deal with unmeasured premise variables in UI observer design for discrete-time TS fuzzy systems....

2020 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), May 2020, Cluj-Napoca, Romania. pp.1-6, ⟨10.1109/AQTR49680.2020.9129929⟩. ⟨hal-03406040⟩

  • COMM

Using Machine Learning Models to Predict the Length of Stay in a Hospital Setting

Rachda Naila Mekhaldi, Patrice Caulier, Sondès Chaabane, Abdelahad Chraibi, Sylvain Piechowiak

Proper prediction of Length Of Stay (LOS) has become increasingly important these years. The LOS prediction provides better services, managing hospital resources and controls their costs. In this paper , we compared two Machine Learning (ML) methods on the Microsoft available dataset. This data are...

8th World Conference on Information Systems and Technologies (WorldCIST’2020), Apr 2020, Budva, Montenegro. pp.202-211, ⟨10.1007/978-3-030-45688-7_21⟩. ⟨hal-03381824⟩

  • COUV

Using Machine Learning Models to Predict the Length of Stay in a Hospital Setting

Rachda Naila Mekhaldi, Patrice Caulier, Sondès Chaabane, Abdelahad Chraibi, Sylvain Piechowiak

Proper prediction of Length Of Stay (LOS) has become increasingly important these years. The LOS prediction provides better services, managing hospital resources and controls their costs. In this paper, we implemented and compared two Machine Learning (ML) methods, the Random Forest (RF) and the...

Trends and Innovations in Information Systems and Technologies, 1159, Springer International Publishing, pp.202-211, 2020, Advances in Intelligent Systems and Computing, 978-3-030-45688-7. ⟨10.1007/978-3-030-45688-7_21⟩. ⟨hal-03696678⟩