Data mining of effect sizes from PubMed abstracts: a cross-study conceptual replication. - Paul Monsarrat; Jean-Noel Vergnes (Bioinform., 2018)

The progressive substitution of hazard ratios for relative risks in biomedical research. - Paul Monsarrat; Jean-Noel Vergnes (Scientometrics, 2019)

A Comparative Study of Additive Local Explanation Methods based on Feature Influences. - Emmanuel Doumard; Julien Aligon; Elodie Escriva; Jean-Baptiste Excoffier; Paul Monsarrat; Chantal Soulé-Dupuy (DOLAP, 2022)

How to Make the Most of Local Explanations: Effective Clustering Based on Influences. - Elodie Escriva; Julien Aligon; Jean-Baptiste Excoffier; Paul Monsarrat; Chantal Soulé-Dupuy (ADBIS, 2023)

Data Exploration Based on Local Attribution Explanation: A Medical Use Case. - Elodie Escriva; Emmanuel Doumard; Jean-Baptiste Excoffier; Julien Aligon; Paul Monsarrat; Chantal Soulé-Dupuy (ADBIS (Short Papers), 2023)

Databases and Information Systems: Contributions from ADBIS 2023 Workshops and Doctoral Consortium. - Adam Przybylek; Aleksandra Karpus; Allel Hadjali; Anton Dignös; Carmem S. Hara; Danae Pla Karidi; Ester Zumpano; Fabio Persia; Genoveva Vargas-Solar; George Papastefanatos; Giancarlo Sperlì; Giorgos Giannopoulos; et al. (ADBIS (Short Papers), 2023)

A quantitative approach for the comparison of additive local explanation methods. - Emmanuel Doumard; Julien Aligon; Elodie Escriva; Jean-Baptiste Excoffier; Paul Monsarrat; Chantal Soulé-Dupuy (Inf. Syst., 2023)

Explanations as a New Metric for Feature Selection: A Systematic Approach. - Haomiao Wang; Emmanuel Doumard; Chantal Soulé-Dupuy; Philippe Kémoun; Julien Aligon; Paul Monsarrat (IEEE J. Biomed. Health Informatics, 2023)

Effective data exploration through clustering of local attributive explanations. - Elodie Escriva; Tom Lefrere; Manon Martin; Julien Aligon; Alexandre Chanson; Jean-Baptiste Excoffier; Nicolas Labroche; Chantal Soulé-Dupuy; Paul Monsarrat (Inf. Syst., 2025)

auto-xFS: An explanation-based feature selection tool for more meaningful and trustworthy machine learning models. - Haomiao Wang; Julien Aligon; Haoran Zhou; Chantal Soulé-Dupuy; Paul Monsarrat (SoftwareX, 2025)