Sfoglia per Corso Dottorato nazionale in intelligenza artificiale
Advancing AI in Healthcare Through Federated Continual Learning
2025
Advancing Radiology with Multimodal Deep Learning: From Automated Reporting to Comprehensive Diagnostic Insights
2025
Application of Artificial Intelligence models in Public Health for the study of the interaction between exposome, biological aging, and maternal-child health
2025
Artificial Intelligence Applications to Lower Limb Rehabilitation Robotics
2026
Artificial Intelligence in Arrhythmology
2025
Beyond Local Regulation: Network-Based Prediction of Gene Expression and Its Application to Neuropsychiatric Traits
2025
Beyond The Genome: Integrative Multi-omic Analysis Of Complex Traits Using Biobank Data
2026
Counterfactual-based Recommendations for Prevention of High-Prevalence Chronic Diseases
2026
Deep Learning-Driven Classification of NSCLC Histological Subtypes Using PET and CT Imaging
2026
Deep Reinforcement Learning and Edge Computing for Type-1 Diabetes Management
2025
Design and Analysis of Cloud Edge Architectures for the Development and Deployment of Distributed AI Application in Health Domain
2025
Enhancing Neoantigen Identification: The Role of Artificial Intelligence and Proteogenomics in Personalized Cancer Therapy
2025
Enhancing Predictive Models in Lung Cancer with Unstructured EHR and Multi-Modal Data Fusion
2026
Exploring Artificial Intelligence Technologies for Automatic Speech Recognition in Voice Disorders
2025
Exploring biological network structures: aquatic food webs and contact networks
2025
Exploring Machine Learning for Image Enhancement and Multimedia Understanding towards Autistic People’s behavior analysis
2025
From AI for Personalized Medicine to Ethical Model Transparency: A Journey Through Explainable AI, Model Editing, and Bias Mitigation
2026
From Human Cognition to Continual Learning: Neural Selectivity, Memory Consolidation and Dreaming
2026
How Data Organization Shapes Neural Network Learning: Hierarchical Labels and Spectral Structure
2026
Implementing machine-learning techniques to study inter-individual variability in fMRI-related brain cognitive functions
2026
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