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1.
Sacituzumab govitecan vs. chemotherapy for metastatic breast cancer: a meta-analysis on safety outcomes.
Future Oncol
; : 1-8, 2024 Jun 12.
Artículo
en Inglés
| MEDLINE | ID: mdl-38864297
2.
Eribulin Mesylate as Third or Subsequent Line Chemotherapy for Elderly Patients with Locally Recurrent or Metastatic Breast Cancer: A Multicentric Observational Study of GIOGer (Italian Group of Geriatric Oncology)-ERIBE.
Oncologist
; 24(6): e232-e240, 2019 06.
Artículo
en Inglés
| MEDLINE | ID: mdl-30413667
3.
Efficacy and safety of lenvatinib in an elderly patient with metastatic papillary thyroid carcinoma and cardiological comorbidity: a case report.
Future Oncol
; 15(24s): 27-33, 2019 Aug.
Artículo
en Inglés
| MEDLINE | ID: mdl-31393171
4.
Dose intensity and efficacy of the combination of everolimus and exemestane (EVE/EXE) in a real-world population of hormone receptor-positive (ER+/PgR+), HER2-negative advanced breast cancer (ABC) patients: a multicenter Italian experience.
Breast Cancer Res Treat
; 163(3): 587-594, 2017 Jun.
Artículo
en Inglés
| MEDLINE | ID: mdl-28353061
5.
Efficacy and safety of eribulin in taxane-refractory patients in the 'real world'.
Future Oncol
; 13(11): 971-978, 2017 May.
Artículo
en Inglés
| MEDLINE | ID: mdl-28326833
6.
Explainable 3D CNN based on baseline breast DCE-MRI to give an early prediction of pathological complete response to neoadjuvant chemotherapy.
Comput Biol Med
; 172: 108132, 2024 Apr.
Artículo
en Inglés
| MEDLINE | ID: mdl-38508058
7.
Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer.
Sci Rep
; 13(1): 8575, 2023 05 26.
Artículo
en Inglés
| MEDLINE | ID: mdl-37237020
8.
Prognostic power assessment of clinical parameters to predict neoadjuvant response therapy in HER2-positive breast cancer patients: A machine learning approach.
Cancer Med
; 12(22): 20663-20669, 2023 11.
Artículo
en Inglés
| MEDLINE | ID: mdl-37905688
9.
Analyzing breast cancer invasive disease event classification through explainable artificial intelligence.
Front Med (Lausanne)
; 10: 1116354, 2023.
Artículo
en Inglés
| MEDLINE | ID: mdl-36817766
10.
Downstream Signaling of Inflammasome Pathway Affects Patients' Outcome in the Context of Distinct Molecular Breast Cancer Subtypes.
Pharmaceuticals (Basel)
; 15(6)2022 May 24.
Artículo
en Inglés
| MEDLINE | ID: mdl-35745570
11.
An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients' Age: A Retrospective Cohort Study.
Cancers (Basel)
; 14(9)2022 Apr 28.
Artículo
en Inglés
| MEDLINE | ID: mdl-35565344
12.
Adenosine pathway inhibitors: novel investigational agents for the treatment of metastatic breast cancer.
Expert Opin Investig Drugs
; 31(7): 707-713, 2022 Jul.
Artículo
en Inglés
| MEDLINE | ID: mdl-35575038
13.
Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy.
J Pers Med
; 12(6)2022 Jun 10.
Artículo
en Inglés
| MEDLINE | ID: mdl-35743737
14.
A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification.
PLoS One
; 17(9): e0274691, 2022.
Artículo
en Inglés
| MEDLINE | ID: mdl-36121822
15.
A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients.
Sci Rep
; 12(1): 7914, 2022 05 12.
Artículo
en Inglés
| MEDLINE | ID: mdl-35552476
16.
Decision support systems for the prediction of lymph node involvement in early breast cancer.
J BUON
; 26(1): 275-277, 2021.
Artículo
en Inglés
| MEDLINE | ID: mdl-33721462
17.
Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.
Cancers (Basel)
; 13(2)2021 Jan 19.
Artículo
en Inglés
| MEDLINE | ID: mdl-33477893
18.
Advancement study of CancerMath model as prognostic tools for predicting Sentinel lymph node metastasis in clinically negative T1 breast cancer patients.
J BUON
; 26(3): 720-727, 2021.
Artículo
en Inglés
| MEDLINE | ID: mdl-34268926
19.
Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs.
Sci Rep
; 11(1): 14123, 2021 07 08.
Artículo
en Inglés
| MEDLINE | ID: mdl-34238968
20.
Early Prediction of Breast Cancer Recurrence for Patients Treated with Neoadjuvant Chemotherapy: A Transfer Learning Approach on DCE-MRIs.
Cancers (Basel)
; 13(10)2021 May 11.
Artículo
en Inglés
| MEDLINE | ID: mdl-34064923