SAE: An R package for early stopping rules in clinical trials. - Caroline Bascoul-Mollevi; Agnès Laplanche; Marie Cécile Le Deley; Andrew Kramar (Comput. Methods Programs Biomed., 2011)

Breast Cancer and Quality of Life: Medical Information Extraction from Health Forums. - Thomas Opitz 001; Jérôme Azé; Sandra Bringay; Cyrille Joutard; Christian Lavergne; Caroline Mollevi (MIE, 2014)

Construction d'un vocabulaire patient/médecin dédié au cancer du sein à partir des médias sociaux. - Mike Donald Tapi-Nzali; Sandra Bringay; Christian Lavergne; Thomas Opitz 001; Jérôme Azé; Caroline Mollevi (IC, 2015)

Explain Sentiments using Conditional Random Field and a Huge Lexical Network. - Mike Donald Tapi-Nzali; Sandra Bringay; Pierre Pompidor; Joël Maïzi; Christian Lavergne; Caroline Mollevi (SIMBig, 2015)

Formalisation semi-automatique d'un vocabulaire patient/médecin dédié au cancer du sein. - Mike Donald Tapi-Nzali; Jérôme Azé; Sandra Bringay; Christian Lavergne; Caroline Mollevi; Thomas Opitz 001 (Rev. d'Intelligence Artif., 2016)

Longitudinal health-related quality of life analysis in oncology with time to event approaches, the STATA command qlqc30_TTD. - Caroline Bascoul-Mollevi; Marion Savina; Amélie Anota; Antoine Barbieri; David Azria; Franck Bonnetain; Sophie Gourgou (Comput. Methods Programs Biomed., 2018)

Reconciliation of patient/doctor vocabulary in a structured resource. - Mike Donald Tapi-Nzali; Jérôme Azé; Sandra Bringay; Christian Lavergne; Caroline Mollevi; Thomas Optiz (Health Informatics J., 2019)

GUIP1: a R package for dose escalation strategies in phase I cancer clinical trials. - Derek Dinart; Julien Fraisse; Diego Tosi; Audrey Mauguen; Célia Touraine; Sophie Gourgou; Marie Cécile Le Deley; Carine Bellera; Caroline Mollevi (BMC Medical Informatics Decis. Mak., 2020)

EBBE-Text : Visualisation de la frontière de décision des réseaux de neurones en classification automatique de textes. - Alexis Delaforge; Jérôme Azé; Arnaud Sallaberry; Maximilien Servajean; Sandra Bringay; Caroline Mollevi (EGC, 2021)

Expliquer les prédictions des réseaux de neurones par l'exploration de l'espace de représentation et de la frontière de décision à l'aide d'EBBE-Text. - Alexis Delaforge; Jérôme Azé; Arnaud Sallaberry; Maximilien Servajean; Sandra Bringay; Caroline Mollevi (EGC, 2021)

Controversy Detection: A Text and Graph Neural Network Based Approach. - Samy Benslimane; Jérôme Azé; Sandra Bringay; Maximilien Servajean; Caroline Mollevi (WISE (1), 2021)

%TTD and %TUDD: New SAS macro programs to calculate the survival data of the time to deterioration for patient-reported outcomes data in oncology. - Emilie Charton; A. Falcoz; E. François; Célia Touraine; J.-B. Bachet; C. Louvet; Z. Hamidou; Caroline Bascoul-Mollevi; Amélie Anota (Comput. Methods Programs Biomed., 2022)

Détection de la controverse : une approche basée sur les réseaux de neurones, appliquée aux graphes et aux textes. - Samy Benslimane; Jérôme Azé; Sandra Bringay; Caroline Mollevi; Maximilien Servajean (CNIA, 2023)

Explaining controversy through community analysis on Twitter. - Samy Benslimane; Thomas Papastergiou; Jérôme Azé; Sandra Bringay; Caroline Mollevi; Maximilien Servajean (IDEAS, 2023)

A text and GNN based controversy detection method on social media. - Samy Benslimane; Jérôme Azé; Sandra Bringay; Maximilien Servajean; Caroline Mollevi (World Wide Web (WWW), 2023)

EBBE-Text: Explaining Neural Networks by Exploring Text Classification Decision Boundaries. - Alexis Delaforge; Jérôme Azé; Sandra Bringay; Caroline Mollevi; Arnaud Sallaberry; Maximilien Servajean (IEEE Trans. Vis. Comput. Graph., 2023)

A SHAP-based controversy analysis through communities on Twitter. - Samy Benslimane; Thomas Papastergiou; Jérôme Azé; Sandra Bringay; Maximilien Servajean; Caroline Mollevi (World Wide Web (WWW), 2024)