Evaluating Explanations of an Alzheimer's Disease 18F-FDG Brain PET Black-Box Classifier. - Lisa Anita De Santi; Filippo Bargagna; Maria Filomena Santarelli; Vincenzo Positano (xAI (1), 2023)

An Explainable Convolutional Neural Network for the Early Diagnosis of Alzheimer's Disease from 18F-FDG PET. - Lisa Anita De Santi; Elena Pasini; Maria Filomena Santarelli; Dario Genovesi; Vincenzo Positano (J. Digit. Imaging, 2023)

Left Ventricle Detection from Cardiac Magnetic Resonance Relaxometry Images Using Visual Transformer. - Lisa Anita De Santi; Antonella Meloni; Maria Filomena Santarelli; Laura Pistoia; Anna Spasiano; Tommaso Casini; Maria Caterina Putti; Liana Cuccia; Filippo Cademartiri; Vincenzo Positano (Sensors, 2023)

Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios. - Filippo Bargagna; Lisa Anita De Santi; Nicola Martini; Dario Genovesi; Brunella Favilli; Giuseppe Vergaro; Michele Emdin; Assuero Giorgetti; Vincenzo Positano; Maria Filomena Santarelli (J. Digit. Imaging, 2023)

Bayesian XAI Methods Towards a Robustness-Centric Approach to Deep Learning: An ABIDE I Study. - Filippo Bargagna; Lisa Anita De Santi; Maria Filomena Santarelli; Vincenzo Positano; Nicola Vanello (MeMeA, 2024)

PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans. - Lisa Anita De Santi; Jörg Schlötterer; Michael Scheschenja; Joel Wessendorf; Meike Nauta; Vincenzo Positano; Christin Seifert (ISIC/iMIMIC/EARTH/DeCaF@MICCAI, 2024)

Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer's Disease classification. - Lisa Anita De Santi; Jörg Schlötterer; Meike Nauta; Vincenzo Positano; Christin Seifert (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)