82 citations · 138 across the 10 of their papers we have counts for
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Resilient Vision-Tabular Multimodal Learning under Modality Missingness
Camillo Maria Caruso, Valerio Guarrasi, Paolo Soda
Multimodal deep learning has shown strong potential in medical applications by integrating heterogeneous data sources such as medical images and structured clinical variables. Howe…
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…