FAIR
National PNRR partnership for human-centred and resilient artificial intelligence, including ArCo's work on robust multimodal biomedical AI.
National Partnership
FAIR
National PNRR partnership for human-centred and resilient artificial intelligence, including ArCo's work on robust multimodal biomedical AI.
Overview
FAIR is the Italian PNRR extended partnership dedicated to Future Artificial Intelligence Research. The programme addresses core AI challenges including human-centred interaction, integration across data sources, resilience, adaptability, quality, sustainability, and bio-inspired intelligence.
Within this national ecosystem, ArCo contributes to the Resilient AI line with expertise in multimodal biomedical AI, explainable decision support, missing modalities, adversarial robustness, fairness, and robust learning for medical data collected in real-world clinical settings.
Research Directions
- Human-centred AI methods designed to collaborate with people and operate in evolving contexts.
- Robust and resilient learning under noisy, incomplete, inconsistent, and real-world data.
- Data augmentation, adversarial robustness, fairness, and multimodal representation learning for biomedical case studies.
Related Publications
- Beyond a single mode: GAN ensembles for diverse medical data generation2026generative AI medical imaging
- Predicting lung cancer survival with attention-based CT slices combination2026
- XGeM: A multi-prompt foundation model for multimodal medical data generation2026foundation models generative AI multimodal learning
- Cross-Dataset Multivariate Time-Series Model for Parkinson’s Diagnosis via Keyboard Dynamics2026foundation models medical imaging
- LatentAugment: Data Augmentation via Guided Manipulation of GAN’s Latent Space2025generative AI multimodal learning
- Towards a Sustainable Future: AI-Powered Solutions in Agriculture and Green Energy2025industrial AI generative AI
- Next-Gen Health: from Multimodal AI to Foundation Models2025foundation models generative AI multimodal learning medical imaging
- Evaluating Vision Language Model Adaptations for Radiology Report Generation in Low-Resource Languages2025foundation models medical imaging
- Benchmarking foundation models and parameter-efficient fine-tuning for prognosis prediction in medical imaging2025foundation models clinical prediction medical imaging
- Lesion-Aware Generative Artificial Intelligence for Virtual Contrast-Enhanced Mammography in Breast Cancer2025radiomics oncology generative AI
- Augmented intelligence for multimodal virtual biopsy in breast cancer using generative artificial intelligence2025oncology multimodal learning generative AI
- Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs2025oncology foundation models generative AI
- Any-to-Any Vision-Language Model for Multimodal X-ray Imaging and Radiological Report Generation2025foundation models medical imaging generative AI
- Benchmarking GAN-Based vs Classical Data Augmentation on Biomedical Images2025
- Whole-Body Image-to-Image Translation for a Virtual Scanner in a Healthcare Digital Twin2025medical imaging generative AI
- Timing Is Everything: Finding the Optimal Fusion Points in Multimodal Medical Imaging2025multimodal learning medical imaging
- Beyond unimodal analysis: Multimodal ensemble learning for enhanced assessment of atherosclerotic disease progression2025multimodal learning clinical prediction
- A systematic review of intermediate fusion in multimodal deep learning for biomedical applications2025multimodal learning
- Class balancing diversity multimodal ensemble for Alzheimer’s disease diagnosis and early detection2025clinical prediction multimodal learning
- Texture-Aware StarGAN for CT data harmonization2025generative AI medical imaging
- Transformer-based AI approach to unravel long-term, time-dependent prognostic complexity in patients with advanced NSCLC and PD-L1 ≥50%: insights from the pembrolizumab 5-year global registry2025clinical prediction oncology explainability
- MARIA: A multimodal transformer model for incomplete healthcare data2025multimodal learning foundation models clinical prediction
- Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer2025clinical prediction explainability multimodal learning
- Doctor-in-the-Loop: An explainable, multi-view deep learning framework for predicting pathological response in non-small cell lung cancer2025explainability clinical prediction medical imaging
- Can Foundation Models Really Segment Tumors? A Benchmarking Odyssey in Lung CT Imaging2025foundation models medical imaging
- Multi-stage intermediate fusion for multimodal learning to classify non-small cell lung cancer subtypes from CT and PET2025radiomics oncology multimodal learning
- Multi-Dataset Multi-Task Learning for COVID-19 Prognosis2024COVID-19 clinical prediction multimodal learning
- A deep learning approach for virtual contrast enhancement in Contrast Enhanced Spectral Mammography2024medical imaging generative AI
- An optimized ensemble search approach for classification of higher-level gait disorder using brain magnetic resonance images2024medical imaging clinical prediction
- Multimodal explainability via latent shift applied to COVID-19 stratification2024explainability multimodal learning COVID-19
- Multi input–Multi output 3D CNN for dementia severity assessment with incomplete multimodal data2024
- Cross-Modality Calibration in Multi-Input Network for Axillary Lymph Node Metastasis Evaluation2024radiomics oncology multimodal learning
- Machine learning predicts pulmonary Long Covid sequelae using clinical data2024clinical prediction
- A deep learning approach for overall survival prediction in lung cancer with missing values2024clinical prediction oncology
- Toward a Multimodal Deep Learning Approach for Histological Subtype Classification in NSCLC2024oncology multimodal learning medical imaging
- RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy2023radiomics oncology multimodal learning
- Named Entity Recognition in Italian Lung Cancer Clinical Reports using Transformers2023oncology foundation models medical imaging
- Early Experiences on using Triplet Networks for Histological Subtype Classification in Non-Small Cell Lung Cancer2023radiomics oncology medical imaging
- Temporal Multimodal Multitask Attention for Affective State Estimation in a Stressful Environment