output
20232026
most citedA Deep Learning Approach for Virtual Contrast Enhancement in Contrast Enhanced Spectral Mammography

35 citations

8 papers

cs.CV2026★ 1 cited

Handling Missing Modalities in Multimodal Survival Prediction for Non-Small Cell Lung Cancer

Filippo Ruffini, Camillo Maria Caruso, Claudia Tacconi +16

Accurate survival prediction in Non-Small Cell Lung Cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Multimodal Deep Learning (MDL) can impro…

cs.CV2025★ 1 cited

Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer

Alice Natalina Caragliano, Claudia Tacconi, Carlo Greco +7

This study proposes a novel approach combining Multimodal Deep Learning with intrinsic eXplainable Artificial Intelligence techniques to predict pathological response in non-small…

cs.LG2025★ 11 cited

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…

eess.IV2025★ 3 cited

Augmented Intelligence for Multimodal Virtual Biopsy in Breast Cancer Using Generative Artificial Intelligence

Aurora Rofena, Claudia Lucia Piccolo, Bruno Beomonte Zobel +2

Full-Field Digital Mammography (FFDM) is the primary imaging modality for routine breast cancer screening; however, its effectiveness is limited in patients with dense breast tissu…

cs.AI2025★ 5 cited

XGeM: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation

Daniele Molino, Francesco Di Feola, Eliodoro Faiella +5

The adoption of Artificial Intelligence in medical imaging holds great promise, yet it remains hindered by challenges such as data scarcity, privacy concerns, and the need for robu…

cs.CV2024★ 26 cited

Class Balancing Diversity Multimodal Ensemble for Alzheimer's Disease Diagnosis and Early Detection

Arianna Francesconi, Lazzaro di Biase, Donato Cappetta +4

Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence and associated societal costs. Early detection and diagnosis of AD are critical…