2 citations · 2 across the 5 of their papers we have counts for
5 papers
Informative Missingness to Generate Irregular Clinical Time Series
Hadi Mehdizavareh, Gabriele Santangelo, Giovanna Nicora +4
Laboratory tests in electronic health records are collected irregularly, and the absence of a test order can be as informative as the measurement itself. Such missingness reflects…
Longitudinal Missing Data Imputation for Predicting Disability Stage of Patients with Multiple Sclerosis
Mahin Vazifehdan, Pietro Bosoni, Daniele Pala +4
Multiple Sclerosis (MS) is a chronic disease characterized by progressive or alternate impairment of neurological functions (motor, sensory, visual, and cognitive). Predicting dise…
Exploring the Impact of Environmental Pollutants on Multiple Sclerosis Progression
Elena Marinello, Erica Tavazzi, Enrico Longato +14
Multiple Sclerosis (MS) is a chronic autoimmune and inflammatory neurological disorder characterised by episodes of symptom exacerbation, known as relapses. In this study, we inves…
Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis
Lorenzo Peracchio, Giovanna Nicora, Enea Parimbelli +5
Applying Artificial Intelligence (AI) and Machine Learning (ML) in critical contexts, such as medicine, requires the implementation of safety measures to reduce risks of harm in ca…
CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: a clinically-inspired deep learning pipeline
Alessia Gerbasi, Arianna Dagliati, Giuseppe Albi +7
The standard non-invasive imaging technique used to assess the severity and extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography Angiography (CCTA). However, man…