INRIA Monc Team

[En tête-à-tête avec] Olivier Saut, un #mathématicien qui travaille sur le #cancer ! Directeur de recherche au @CNRS et Responsable de l'équipe @MoncTeam, il travaille sur la modélisation et l’IA en #oncologie pour aider à la prise en charge des #cancers. bit.ly/3rfCcve

Open postdoc position under my supervision for quantitative modeling of response to #immunotherapy in lung cancer using a large data set with high-dimensional, longitudinal data from the #PIONeeR clinical study. jobs.inria.fr/public/classic…

Finally, the mechanistic model provides a way to give individual simulations and predictions about the invisible metastatic state at diagnosis

For prediction, the mechanistic model revealed as good (if not better) than classical machine learning algorithms and Cox regression. Importantly, the MM could inform on the biological meaning of covariates (i.e. Ki67 on growth, EGFR on dissemination)

The mechanistic model was able to accurately fit the time-to-event data, using mixed-effects learning for inter-individual variability

Leveraging a database with 21 clinicopathologic variables in 642 patients with no adjuvant treatment, we used random survival forest algorithms to select the set of most informative features (Ki67, tumor size, age, EGFR and CD44)

We used a mechanistic model for time-to-recurrence based on two biological processes: growth and dissemination

Last publication "Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer" #MachineLearning #mathonco Collab @Inria_Bordeaux @MoncTeam @sistmteam @BERGONIE33 ascopubs.org/doi/10.1200/CC…

📣#Écolgie et #Numérique : comprendre et agir ! Conférence-débat le 28/01 à 18h30, Bât A22 amphi Wegener, campus Peixotto. ACollin, JChabassier @Inria_Bordeaux @universite_uppa @univbordeaux @BordeauxINP #ecoinfo

New preprint using an integrative approach to identify molecular determinants of metastasis in kidney cancer. Used lots of -omics analysis and #mathonco modeling of MRI data. Huge work led by @AndreasBikfalvi. @MoncTeam disq.us/t/3lak9r2

A message to all our #bordeaux #cancer scientists who are not on Twitter... so won't read this tweet... 😕 @univbordeaux @BERGONIE33 @CHUBordeaux @Inserm @CNRSAquitaine @inserm_u1035 @ImmunoConcept

Postdoc position available in my group about mathematical modeling of the biology of metastasis in kidney cancer from functional, imaging and genomics data. Please contact me if interested: jobs.inria.fr/public/classic…

We’re hiring! Two post-doc positions - on modeling and AI against glioma - are already available and more to come in @MoncTeam at @Inria_Bordeaux jobs.inria.fr/public/classic… jobs.inria.fr/public/classic…

Next it's @SBenzekry presenting Machine learning versus mechanistic modeling for prediction of metastatic relapse in breast cancer #mathonc19

Next up is @SBenzekry to tell us about combining machine learning and mechanistic modeling to predict metastatic relapse in breast cancer #mathonc19

A midi ce mercredi 15.05, rdv à l'amphithéâtre de l'Institut de mathématiques de @univbordeaux A33 pour le cycle de sémainaire de l'#oncosphère avec @AndreasBikfalvi et V.Vendrely. Retransmission en direct sur rendez-vous.renater.fr/oncosphere

L’équipe MONC (Inria Bx @CNRS @BordeauxINP) et @SOPHiAGENETICS, permettront, grâce à de nouveaux modèles mathématiques et au #MachineLearning, de mieux appréhender le suivi patients et de définir les stratégies thérapeutiques les + adaptées. via @INRIA bit.ly/2TwYohW

@dbasanta @SBenzekry @JeSuisOS @Inria_Bordeaux Thanks David!!

The @MoncTeam is awarded 900k€ from MSD for a project combining #mathonco and #AI to help personalize #NSCLC treatment! A project lead by @JeSuisOS. #radiomics @Inria_Bordeaux inria.fr/actualite/actu…