Bioinformatics modelling of baseline characteristics to predict clinical outcomes and responses in the LixiLan-L trial
Event: International Diabetes Federation (IDF) Congress, Abu Dhabi, UAE Authors: P. Fogel, A. Civet, T. Fan, A. Shaunik, C. Brulle-Wohlhueter, Y. Gaston-Mathe View Poster Background Identifying categories of patients with diabetes sharing common characteristics and analysing clinical outcomes in these groups may lead to better understanding of patient diversity and generate hypotheses on disease-driving mechanisms. […]
Using machine learning algorithms to identify predictive factors of clinical outcomes with iGlarLixi or iGlar in the LixiLan-L trial
Event: Annual Meeting of the European Association for the Study of Diabetes (EASD) 2017, Lisbon, Portugal Authors: Y. Gaston-Mathé, T. Fan, A. Shaunik, C.Brulle-Wohlhueter, A. Civet View Poster
MMS19 as a potential predictive marker of adjuvant chemotherapy benefit in resected non-small cell lung cancer
Publisher: Cancer BiomarkersAuthors: J. Adam, T. Sourisseau, K.A. Olaussen, A. Robin, C.Q. Zhu, A. Templier, A. Civet, P. Girard, V. Lazar, P. Validire, M. S. Tsao, J.-C. Soria, B. Besse View publication Background Resectable non-small cell lung cancer (NSCLC) treatment options most often consist of surgical resection along with adjuvant chemotherapy (ACT). The benefit of ACT however […]
