Domenico Pomarico

Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study

A. Paradiso, R. Massafra, A. Zito, 2021, Cancers.

Sentinel Lymph Node Metastasis on Clinically Negative Patients: Preliminary Results of a Machine Learning Model Based on Histopathological Features

M. C. Comes, A. Paradiso, R. Massafra, 2021, Applied Sciences.

Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy

M. C. Comes, A. Paradiso, R. Massafra, 2022, Journal of personalized medicine.

A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients

M. C. Comes, R. Massafra, A. Zito, 2022, Scientific Reports.

A Proposal of Quantum-Inspired Machine Learning for Medical Purposes: An Application Case

Nicola Amoroso, Roberto Bellotti, Annarita Fanizzi, 2021, Mathematics.

A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification

M. C. Comes, R. Massafra, A. Zito, 2022, PloS one.

A Roadmap towards Breast Cancer Therapies Supported by Explainable Artificial Intelligence

N. Amoroso, A. Monaco, R. Bellotti, 2021, Applied Sciences.

Analyzing breast cancer invasive disease event classification through explainable artificial intelligence

M. C. Comes, N. Amoroso, R. Bellotti, 2023, Frontiers in Medicine.

Decision support systems for the prediction of lymph node involvement in early breast cancer.

R. Massafra, A. Fanizzi, V. Didonna, 2021, Journal of B.U.ON. : official journal of the Balkan Union of Oncology.

Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer

M. C. Comes, R. Massafra, A. Zito, 2023, Scientific reports.