Cyrille Delpierre

A Single-Graph Visualization to Reveal Hidden Explainability Patterns of SHAP Feature Interactions in Machine Learning for Biomedical Issues

The paper introduces a visualization method to analyze SHAP feature interactions in ML models for biomedical applications, revealing hidden patterns of explainability.

Discernibility in explanations: an approach to designing more acceptable and meaningful machine learning models for medicine

This paper introduces discernibility as a metric to evaluate the clarity of explanations in machine learning models for medicine, finding that the dcor metric best captures user-perceived relationships between data and explanations.

Strain-specific changes in nucleus accumbens transcriptome and motivation for food reward in mice exposed to maternal separation

The paper shows that maternal separation in C3H/HeN mice increases motivation for palatable food and alters nucleus accumbens gene expression, while C57Bl/6J mice show no such changes.