Francesco Prinzi

According to our database, Francesco Prinzi authored at least 12 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Using AI explainable models and handwriting/drawing tasks for psychological well-being.

Francesco Prinzi, Pietro Barbiero, Claudia Greco, Terry Amorese, Gennaro Cordasco, Pietro Liò, Salvatore Vitabile, Anna Esposito

Inf. Syst., 2025

2024

A Yolo-Based Model for Breast Cancer Detection in Mammograms.

Francesco Prinzi, Marco Insalaco, Alessia Orlando, Salvatore Gaglio, Salvatore Vitabile

Cogn. Comput., January, 2024

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Yang Nan, Xiaodan Xing, Shiyi Wang, Zeyu Tang, Federico N. Felder, Sheng Zhang, Roberta Eufrasia Ledda, Xiaoliu Ding, Ruiqi Yu, Weiping Liu, Feng Shi, Tianyang Sun, Zehong Cao, Minghui Zhang, Yun Gu, Hanxiao Zhang, Jian Gao, Pingyu Wang, Wen Tang, Pengxin Yu, Han Kang, Junqiang Chen, Xing Lu, Boyu Zhang, Michail Mamalakis, Francesco Prinzi, Gianluca Carlini, Lisa Cuneo, Abhirup Banerjee, Zhaohu Xing, Lei Zhu, Zacharia Mesbah, Dhruv Jain, Tsiry Mayet, Hongyu Yuan, Qing Lyu, Abdul Qayyum, Moona Mazher, Athol Wells, Simon L. F. Walsh, Guang Yang

Medical Image Anal., 2024

Breast cancer classification through multivariate radiomic time series analysis in DCE-MRI sequences.

Francesco Prinzi, Alessia Orlando, Salvatore Gaglio, Salvatore Vitabile

Expert Syst. Appl., 2024

Rad4XCNN: a new agnostic method for post-hoc global explanation of CNN-derived features by means of radiomics.

Francesco Prinzi, Carmelo Militello, Calogero Zarcaro, Tommaso Vincenzo Bartolotta, Salvatore Gaglio, Salvatore Vitabile

CoRR, 2024

MUGI-MRI: Enhancing Breast Cancer Classification through Multiplex Graph Neural Networks in DCE-MRI.

Francesco Ceccarelli, Francesco Prinzi, Pietro Liò, Salvatore Vitabile, Sean B. Holden

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease.

Carmelo Militello, Francesco Prinzi, Giulia Sollami, Leonardo Rundo, Ludovico La Grutta, Salvatore Vitabile

Cogn. Comput., January, 2023

Transformer-Based Approach to Melanoma Detection.

Giansalvo Cirrincione, Sergio Cannata, Giovanni Cicceri, Francesco Prinzi, Tiziana Currieri, Marta Lovino, Carmelo Militello, Eros Pasero, Salvatore Vitabile

Sensors, 2023

Impact of Wavelet Kernels on Predictive Capability of Radiomic Features: A Case Study on COVID-19 Chest X-ray Images.

Francesco Prinzi, Carmelo Militello, Vincenzo Conti, Salvatore Vitabile

J. Imaging, 2023

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Yang Nan, Xiaodan Xing, Shiyi Wang, Zeyu Tang, Federico N. Felder, Sheng Zhang, Roberta Eufrasia Ledda, Xiaoliu Ding, Ruiqi Yu, Weiping Liu, Feng Shi, Tianyang Sun, Zehong Cao, Minghui Zhang, Yun Gu, Hanxiao Zhang, Jian Gao, Wen Tang, Pengxin Yu, Han Kang, Junqiang Chen, Xing Lu, Boyu Zhang, Michail Mamalakis, Francesco Prinzi, Gianluca Carlini, Lisa Cuneo, Abhirup Banerjee, Zhaohu Xing, Lei Zhu, Zacharia Mesbah, Dhruv Jain, Tsiry Mayet, Hongyu Yuan, Qing Lyu, Athol Wells, Simon Walsh, Guang Yang

CoRR, 2023

Explainable Machine-Learning Models for COVID-19 Prognosis Prediction Using Clinical, Laboratory and Radiomic Features.

Francesco Prinzi, Carmelo Militello, Nicola Scichilone, Salvatore Gaglio, Salvatore Vitabile

IEEE Access, 2023

2022

ML-Based Radiomics Analysis for Breast Cancer Classification in DCE-MRI.

Francesco Prinzi, Alessia Orlando, Salvatore Gaglio, Massimo Midiri, Salvatore Vitabile

AII, 2022