Thematic Session 3

THEMATIC SESSION #3

Selene Tomassini

University of Trento, Italy

• selene.tomassini@unitn.it

Alessia Sarica

Magna Graecia University of Catanzaro, Italy

• sarica@unicz.it

Federica Aracri

Magna Graecia University of Catanzaro, Italy

• federica.aracri@studenti.unicz.it

We are pleased to invite submissions to the Thematic Session (TS) on “AI-Powered Neurology: Enhancing Diagnostic and Prognostic Decision Support”.

This TS will explore innovative research contributions and applications of AI in clinical decision support, with a focus on diagnostics and prognostics for neurological diseases.

We encourage submissions that address technical advancements as well as ethical considerations, including interpretability, transparency, and clinical impact.

Topics of interest include, but are not limited to:

• Neuroimage processing and analysis
• Neuroimage captioning and report generation
• Clinical decision-support systems in neurology, neuro-radiology and neuro-oncology
• AI-driven algorithms for early detection and classification of neurodegenerative diseases
• AI-driven algorithms for automatic segmentation of cancerous lesions in the brain
• Deep learning techniques for neuroanatomical analysis and biomarker discovery
• Machine learning approaches for cognitive impairment and neurodegeneration
• Explainable AI in neuroimaging
• Generative AI in neuroimaging
• Uncertainty quantification and reliability assessment of AI-powered models in neurology
• Data fusion techniques for multi-modal neurological data

Dr. Selene Tomassini got, in 2023, the PhD in Information Engineering curriculum Biomedical, Electronic and Telecommunication Engineering at the Department of Information Engineering of Università Politecnica delle Marche, Italy, defending a thesis entitled “On-cloud decision-support algorithms driven by deep learning in 3D radiological imaging diagnostics”. She is currently Assistant Professor at the Department of Information Engineering and Computer Science of University of Trento, Italy, teaching “Computer science applied to radiological sciences” and “AI in radiodiagnostics and radiotherapy”, and mainly working on designing and developing AI-based models for processing and analysis of medical images, with a focus on clinical decision-support systems in neuro-radiology and diagnostics.

Prof. Alessia Sarica is Associate Professor of Advanced Medical and Surgical Technology and Methodology at the Neuroscience Research Center, Department of Medical and Surgical Sciences at Magna Graecia University of Catanzaro, Italy. She specializes in AI, Explainable AI and interpretable machine learning for neuroimaging and medical diagnostics. Her work emphasizes transparency and ethics in AI, particularly for early diagnosis and progression monitoring of neurodegenerative diseases, including Alzheimer’s and Parkinson’s. With a robust academic portfolio and multiple editorial roles in leading journals, she has pioneered AI-based tools that have significantly impacted clinical classification, with over 65 peer-reviewed publications.

Dr. Federica Aracri got, in 2024, the PhD in Neuroscience curriculum Analysis of Imaging Data, Neurophysiological Biosignals and Molecular Profiling for the Identification of Biomarkers Applied to Neuroscience at the Neuroscience Research Center, Department of Medical and Surgical Sciences at Magna Graecia University of Catanzaro, Italy, defending a thesis entitled “Eye movement disorder in progressive subnuclear paralysis analysis”. She is actually Postdoctoral Research Fellow in “Hybrid PET-MRI to simultaneously probe brain metabolism and cerebrovascular function in neurodegenerative diseases”. She has also experience with missing data management in neurodegenerative disorder data collections.