In patient dose reconstruction using a cine acquisition for dynamic arc radiation therapy. - Angelo Piermattei; Andrea Fidanzio; Luigi Azario; Francesca Greco; Alessandra Mameli; Savino Cilla; Luca Grimaldi; Guido D'Onofrio; Boris Giuseppe Augelli; Gerardina Stimato; Diego Gaudino; Sara Ramella; et al. (Medical Biol. Eng. Comput., 2009)

A Morphing Technique to Estimate Lung Cancer Deformation Due to Breathing in Radiotherapic Treatment. - Grazia Maria Pia Masselli; Luigi Battista; Sergio Silvestri; Sara Ramella; Lucio Trodella (BIOSIGNALS, 2010)

Exploratory Radiomics for Predicting Adaptive Radiotherapy in Non-Small Cell Lung Cancer. - Rosa Sicilia; Ermanno Cordelli; Sara Ramella; Michele Fiore; Carlo Greco; Elisabetta Molfese; Marianna Miele; Enrica Vinciguerra; Patrizia Cornacchione; Edy Ippolito; Rolando Maria D'Angelillo; Giulio Iannello; et al. (CBMS, 2018)

Exploring Deep Pathomics in Lung Cancer. - Charles Z. Liu; Rosa Sicilia; Matteo Tortora; Ermanno Cordelli; Lorenzo Nibid; Giovanna Sabarese; Giuseppe Perrone; Michele Fiore; Sara Ramella; Paolo Soda (CBMS, 2021)

Evaluating GANs in Medical Imaging. - Lorenzo Tronchin; Rosa Sicilia; Ermanno Cordelli; Sara Ramella; Paolo Soda (DGM4MICCAI/DALI@MICCAI, 2021)

Deep Reinforcement Learning for Fractionated Radiotherapy in Non-Small Cell Lung Carcinoma. - Matteo Tortora; Ermanno Cordelli; Rosa Sicilia; Marianna Miele; Paolo Matteucci; Giulio Iannello; Sara Ramella; Paolo Soda (Artif. Intell. Medicine, 2021)

A Multimodal Ensemble Driven by Multiobjective Optimisation to Predict Overall Survival in Non-Small-Cell Lung Cancer. - Camillo Maria Caruso; Valerio Guarrasi; Ermanno Cordelli; Rosa Sicilia; Silvia Gentile; Laura Messina; Michele Fiore; Claudia L. Piccolo; Bruno Beomonte Zobel; Giulio Iannello; Sara Ramella; Paolo Soda (J. Imaging, 2022)

Named Entity Recognition in Italian Lung Cancer Clinical Reports using Transformers. - Domenico Paolo; Alessandro Bria; Carlo Greco; Marco Russano; Sara Ramella; Paolo Soda; Rosa Sicilia (BIBM, 2023)

RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy. - Matteo Tortora; Ermanno Cordelli; Rosa Sicilia; Lorenzo Nibid; Edy Ippolito; Giuseppe Perrone; Sara Ramella; Paolo Soda (IEEE Access, 2023)

Pathologic Complete Response Prediction with Machine Learning Using Hierarchical Attention Feature Extraction. - Domenico Paolo; Ciro Russo; Giulio Russo; Carlo Greco; Alessio Cortellini; Marco Russano; Sara Ramella; Paolo Soda; Claudio Marrocco; Alessandro Bria; Rosa Sicilia (ICPR (Workshops and Challenges, 2), 2024)

Exploring Negated Entites for Named Entity Recognition in Italian Lung Cancer Clinical Reports. - Domenico Paolo; Alessandro Bria; Carlo Greco; Marco Russano; Sara Ramella; Paolo Soda; Rosa Sicilia (pHealth, 2024)

A deep learning approach for overall survival prediction in lung cancer with missing values. - Camillo Maria Caruso; Valerio Guarrasi; Sara Ramella; Paolo Soda (Comput. Methods Programs Biomed., 2024)

Doctor-in-the-Loop: An explainable, multi-view deep learning framework for predicting pathological response in non-small cell lung cancer. - Alice Natalina Caragliano; Filippo Ruffini; Carlo Greco; Edy Ippolito; Michele Fiore; Claudia Tacconi; Lorenzo Nibid; Giuseppe Perrone; Sara Ramella; Paolo Soda; Valerio Guarrasi (Image Vis. Comput., 2025)

Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer. - Alice Natalina Caragliano; Claudia Tacconi; Carlo Greco; Lorenzo Nibid; Edy Ippolito; Michele Fiore; Giuseppe Perrone; Sara Ramella; Paolo Soda; Valerio Guarrasi (CoRR, 2025)

Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs. - Domenico Paolo; Carlo Greco; Alessio Cortellini; Sara Ramella; Paolo Soda; Alessandro Bria; Rosa Sicilia (BMC Medical Informatics Decis. Mak., 2025)