INRIA Monc Team

INRIA Monc Team devoted to Models and AI for Oncology.
Équipe Projet INRIA Monc dédiée à la modélisation et l'IA pour la lutte contre le cancer.

[Oncosphère @OncosphereNA]

[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.
https://t.co/idDPNQPEtC

[Sébastien Benzekry @SBenzekry]

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.
https://t.co/UcUjt4TEQb

[Sébastien Benzekry @SBenzekry]

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

[Sébastien Benzekry @SBenzekry]

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)

[Sébastien Benzekry @SBenzekry]

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

[Sébastien Benzekry @SBenzekry]

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)

[Sébastien Benzekry @SBenzekry]

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

[Sébastien Benzekry @SBenzekry]

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
https://t.co/l1EtQfZZNt

[AcclimaTerra @AcclimaTerra]

📣#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

[Sébastien Benzekry @SBenzekry]

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
https://t.co/2taDP7kRYk

[SIRIC BRIO @SIRICBRIO]

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

[Sébastien Benzekry @SBenzekry]

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: https://t.co/ienk3DIOiS

[INRIA Monc Team @MoncTeam]

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 https://t.co/gF4OyyqpCX https://t.co/3oUFDjdQKF

[Sandy Anderson @ara_anderson]

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

[Kristin R Swanson, PhD @gliomath]

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

[SIRIC BRIO @SIRICBRIO]

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 https://t.co/mmldtMKvra

[Bordeaux INP @BordeauxINP]

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 https://t.co/TFTAnOyPsY

[INRIA Monc Team @MoncTeam]

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