6 papers
Adaptation Interfaces for In-Context Tabular Foundation Models in Time-to-Event Prediction
Minh-Khoi Pham, Luca Cotugno, Dan Cernei +10
Tabular foundation models (TabFMs) achieve strong performance on structured data, particularly for standard classification and regression problems. Yet, extending them to censored…
Tabular Foundation Models for Clinical Survival Analysis via Survival-Aware Adaptation
Minh-Khoi Pham, Luca Cotugno, Alina Sirbu +3
Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis. While classical statistical and…
Knowledge Graph Extraction from Biomedical Literature for Alkaptonuria Rare Disease
Giang Pham, Rebecca Finetti, Caterina Graziani +12
Alkaptonuria (AKU) is an ultra-rare autosomal recessive metabolic disorder caused by mutations in the HGD (Homogentisate 1,2-Dioxygenase) gene, leading to a pathological accumulati…
Machine Learning for analysis of Multiple Sclerosis cross-tissue bulk and single-cell transcriptomics data
Francesco Massafra, Samuele Punzo, Silvia Giulia Galfré +8
Multiple Sclerosis (MS) is a chronic autoimmune disease of the central nervous system whose molecular mechanisms remain incompletely understood. In this study, we developed an end-…
MIEO: encoding clinical data to enhance cardiovascular event prediction
Davide Borghini, Davide Marchi, Angelo Nardone +6
As clinical data are becoming increasingly available, machine learning methods have been employed to extract knowledge from them and predict clinical events. While promising, appro…
A Machine Learning Pipeline for Multiple Sclerosis Biomarker Discovery: Comparing explainable AI and Traditional Statistical Approaches
Samuele Punzo, Silvia Giulia Galfrè, Francesco Massafra +3
We present a machine learning pipeline for biomarker discovery in Multiple Sclerosis (MS), integrating eight publicly available microarray datasets from Peripheral Blood Mononuclea…