A systematic review of intermediate fusion in multimodal deep learning for biomedical applications

V Guarrasi, F Aksu, CM Caruso, F Di Feola… - arxiv preprint arxiv …, 2024 - arxiv.org
Deep learning has revolutionized biomedical research by providing sophisticated methods
to handle complex, high-dimensional data. Multimodal deep learning (MDL) further …

Advancing healthcare through multimodal data fusion: a comprehensive review of techniques and applications

JR Teoh, J Dong, X Zuo, KW Lai, K Hasikin… - PeerJ Computer …, 2024 - peerj.com
With the increasing availability of diverse healthcare data sources, such as medical images
and electronic health records, there is a growing need to effectively integrate and fuse this …

[HTML][HTML] Multimodal explainability via latent shift applied to COVID-19 stratification

V Guarrasi, L Tronchin, D Albano, E Faiella, D Fazzini… - Pattern Recognition, 2024 - Elsevier
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 …

[HTML][HTML] A graph neural network-based model with Out-of-Distribution Robustness for enhancing Antiretroviral Therapy Outcome Prediction for HIV-1

G Di Teodoro, F Siciliano, V Guarrasi… - … Medical Imaging and …, 2025 - Elsevier
Predicting the outcome of antiretroviral therapies (ART) for HIV-1 is a pressing clinical
challenge, especially when the ART includes drugs with limited effectiveness data. This …

[HTML][HTML] Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes

V Guarrasi, P Soda - Computers in Biology and Medicine, 2023 - Elsevier
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 …

[HTML][HTML] An optimized ensemble search approach for classification of higher-level gait disorder using brain magnetic resonance images

K Mogensen, V Guarrasi, J Larsson, W Hansson… - Computers in Biology …, 2025 - Elsevier
Abstract Higher-Level Gait Disorder (HLGD) is a type of gait disorder estimated to affect up
to 6% of the older population. By definition, its symptoms originate from the higher-level …

Machine learning predicts pulmonary Long Covid sequelae using clinical data

E Cordelli, P Soda, S Citter, E Schiavon… - BMC Medical Informatics …, 2024 - Springer
Long COVID is a multi-systemic disease characterized by the persistence or occurrence of
many symptoms that in many cases affect the pulmonary system. These, in turn, may …

Named Entity Recognition in Italian Lung Cancer Clinical Reports using Transformers

D Paolo, A Bria, C Greco, M Russano… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
The widespread adoption of electronic health records (EHRs) offers a valuable opportunity
to support clinical research by containing crucial patient information, including diagnoses …

Early Experiences on using Triplet Networks for Histological Subtype Classification in Non-Small Cell Lung Cancer

F Aksu, F Gelardi, A Chiti, P Soda - 2023 IEEE 36th …, 2023 - ieeexplore.ieee.org
Lung cancer has the highest mortality rate among tumours and an accurate pathological
assessment is crucial to deliver personalized treatments to patients. The gold standard for …

Stage I Stereotactic Body Radiation Therapy Outcome's Prediction Models: Perfection Is the Enemy of Utility

S Ramella, P Soda - Journal of Thoracic Oncology, 2023 - jto.org
The introduction of stereotactic body radiation therapy (SBRT) for patients with early stage
lung cancer definitively increased the chances of survival of a large part of the oncological …