Abstract: Structural Causal Models (SCMs) offer a powerful framework for understanding and reasoning about causal relationships, particularly in the context of total effects. In this presentation, we will explore a […]

Introduction to Weak Supervision & Applications The recent digitization of patient health records and their collection, in a near real-time basis, in Clinical Data Warehouses (CDWs) offer new perspectives for […]

Le Limics porte un axe thématique qui concerne le Médicament. Cet axe utilise les approches d’ingénierie des connaissances et d’intelligence artificielle développées au Limics dans le cadre d’usage autour du […]

MAESTRO will be an integrated pipeline for biomarker discovery and gene expression analysis, combining advanced imaging technologies with spatial transcriptomics (ST) and artificial intelligence (AI). The system will be designed […]

Eduardo Fermé, full professor of computer science at the Universidade da Madeira in Portugal, is spending one month as a visiting researcher at Limics. He is internationally recognized for his […]

Title: Enhancing hematological image analysis with generalizable, interpretable, and adaptable AI models Lieu: Limics, Campus des Cordeliers, salle de conférence Mots-clés : Apprentissage profond,Leucocytes,Explicabilité,Généralisabilité,Classification,Semi-supervision Keywords: Deep Learning,White blood cells,Explainability,Generalisability,Classification,Semi-supervision   Résumé : […]

Thomas Papastergiou est maître de conférence au LIPN, USPN. Ses recherches portent sur l’intelligence artificielle et recouvrent une série d’applications biomédicales allant du diagnostic à la conception de médicaments nouvellement […]