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Plos One|May 2, 2023
A CT-based transfer learning approach to predict NSCLC recurrence: The added-value of peritumoral regionSamantha Bove, Annarita Fanizzi, Federico Fadda, et al.
Cancer Medicine|September 4, 2025
Gender Medicine in Computed Tomography Radiomics Analysis to Predict Disease Progression in Liver Respectable Colorectal Cancer PatientsAnnarita Fanizzi, Arianna Campione, Samantha Bove, et al.
Patterns (New York, N.Y.)|June 28, 2021
NeuriTES. Monitoring neurite changes through transfer entropy and semantic segmentation in bright-field time-lapse microscopyArianna Mencattini, Alida Spalloni, Paola Casti, et al.
Journal of Personalized Medicine|April 30, 2021
Response Predictivity to Neoadjuvant Therapies in Breast Cancer: A Qualitative Analysis of Background Parenchymal Enhancement in DCE-MRIDaniele La Forgia, Angela Vestito, Maurilia Lasciarrea, et al.
Cells|June 24, 2022
Pathological Complete Response to Neoadjuvant Chemoimmunotherapy for Early Triple-Negative Breast Cancer: An Updated Meta-AnalysisAlessandro Rizzo, Antonio Cusmai, Raffaella Massafra, et al.
Healthcare (Basel, Switzerland)|April 13, 2023
A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer PatientsDomenica Antonia Bavaro, Annarita Fanizzi, Serena Iacovelli, et al.
Scientific Reports|November 23, 2023
Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrenceAnnarita Fanizzi, Federico Fadda, Maria Colomba Comes, et al.
Cancers|June 2, 2021
Early Prediction of Breast Cancer Recurrence for Patients Treated with Neoadjuvant Chemotherapy: A Transfer Learning Approach on DCE-MRIsMaria Colomba Comes, Daniele La Forgia, Vittorio Didonna, et al.
Digital Health|February 2, 2026
Enhancing early prediction of pathological complete response in breast cancer using attention-based convolutional neural networks in digital pathologyMaria Colomba Comes, Andrea Lupo, Arianna Bozzi, et al.
Diagnostics (Basel, Switzerland)|April 30, 2021
Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography ImagesRaffaella Massafra, Samantha Bove, Vito Lorusso, et al.
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