82 citations · 380 across the 53 of their papers we have counts for
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Multimodal Explainability via Latent Shift applied to COVID-19 stratification
Valerio Guarrasi, Lorenzo Tronchin, Domenico Albano +4
We are witnessing a widespread adoption of artificial intelligence in healthcare. However, most of the advancements in deep learning in this area consider only unimodal data, negle…
RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy
Matteo Tortora, Ermanno Cordelli, Rosa Sicilia +5
The current cancer treatment practice collects multimodal data, such as radiology images, histopathology slides, genomics and clinical data. The importance of these data sources ta…
Multi-objective optimization determines when, which and how to fuse deep networks: an application to predict COVID-19 outcomes
Valerio Guarrasi, Paolo Soda
The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has bee…