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Prognostic power assessment of clinical parameters to predict neoadjuvant response therapy in HER2-positive breast cancer patients: A machine learning approach.
Fanizzi A, Latorre A, Bavaro DA, Bove S, Comes MC, Di Benedetto EF, Fadda F, La Forgia D, Giotta F, Palmiotti G, Petruzzellis N, Rinaldi L, Rizzo A, Lorusso V, Massafra R. Fanizzi A, et al. Among authors: petruzzellis n. Cancer Med. 2023 Nov;12(22):20663-20669. doi: 10.1002/cam4.6512. Epub 2023 Oct 31. Cancer Med. 2023. PMID: 37905688 Free PMC article.
Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer.
Fanizzi A, Pomarico D, Rizzo A, Bove S, Comes MC, Didonna V, Giotta F, La Forgia D, Latorre A, Pastena MI, Petruzzellis N, Rinaldi L, Tamborra P, Zito A, Lorusso V, Massafra R. Fanizzi A, et al. Among authors: petruzzellis n. Sci Rep. 2023 May 26;13(1):8575. doi: 10.1038/s41598-023-35344-9. Sci Rep. 2023. PMID: 37237020 Free PMC article.
Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography.
Petrillo A, Fusco R, Di Bernardo E, Petrosino T, Barretta ML, Porto A, Granata V, Di Bonito M, Fanizzi A, Massafra R, Petruzzellis N, Arezzo F, Boldrini L, La Forgia D. Petrillo A, et al. Among authors: petruzzellis n. Cancers (Basel). 2022 Apr 25;14(9):2132. doi: 10.3390/cancers14092132. Cancers (Basel). 2022. PMID: 35565261 Free PMC article.
A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients.
Bove S, Comes MC, Lorusso V, Cristofaro C, Didonna V, Gatta G, Giotta F, La Forgia D, Latorre A, Pastena MI, Petruzzellis N, Pomarico D, Rinaldi L, Tamborra P, Zito A, Fanizzi A, Massafra R. Bove S, et al. Among authors: petruzzellis n. Sci Rep. 2022 May 12;12(1):7914. doi: 10.1038/s41598-022-11876-4. Sci Rep. 2022. PMID: 35552476 Free PMC article.