82 citations · 307 across the 37 of their papers we have counts for
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Cross-dataset Multivariate Time-series Model for Parkinson's Diagnosis via Keyboard Dynamics
Arianna Francesconi, Donato Cappetta, Fabio Rebecchi +3
Parkinson's disease (PD) presents a growing global challenge, affecting over 10 million individuals, with prevalence expected to double by 2040. Early diagnosis remains difficult d…
Beyond the Generative Learning Trilemma: Generative Model Assessment in Data Scarcity Domains
Marco Salmè, Lorenzo Tronchin, Rosa Sicilia +2
Data scarcity remains a critical bottleneck impeding technological advancements across various domains, including but not limited to medicine and precision agriculture. To address…
Doctor-in-the-Loop: An Explainable, Multi-View Deep Learning Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer
Alice Natalina Caragliano, Filippo Ruffini, Carlo Greco +8
Non-small cell lung cancer (NSCLC) remains a major global health challenge, with high post-surgical recurrence rates underscoring the need for accurate pathological response predic…
MARIA: a Multimodal Transformer Model for Incomplete Healthcare Data
Camillo Maria Caruso, Paolo Soda, Valerio Guarrasi
In healthcare, the integration of multimodal data is pivotal for developing comprehensive diagnostic and predictive models. However, managing missing data remains a significant cha…
A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications
Valerio Guarrasi, Fatih Aksu, Camillo Maria Caruso +4
Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances th…
Not Another Imputation Method: A Transformer-based Model for Missing Values in Tabular Datasets
Camillo Maria Caruso, Paolo Soda, Valerio Guarrasi
Handling missing values in tabular datasets presents a significant challenge in training and testing artificial intelligence models, an issue usually addressed using imputation tec…
A Deep Learning Approach for Overall Survival Prediction in Lung Cancer with Missing Values
Camillo Maria Caruso, Valerio Guarrasi, Sara Ramella +1
In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevale…