Detalhe da pesquisa
1.
A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis.
BMC Bioinformatics
; 21(Suppl 2): 91, 2020 Mar 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-32164532
2.
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.
Artigo
em Inglês
| MEDLINE | ID: mdl-38508058
3.
Effect of artificial shading on the tannin accumulation and aromatic composition of the Grillo cultivar (Vitis vinifera L.).
BMC Plant Biol
; 13: 175, 2013 Nov 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-24195612
4.
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.
Artigo
em Inglês
| MEDLINE | ID: mdl-37237020
5.
Analyzing breast cancer invasive disease event classification through explainable artificial intelligence.
Front Med (Lausanne)
; 10: 1116354, 2023.
Artigo
em Inglês
| MEDLINE | ID: mdl-36817766
6.
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.
Artigo
em Inglês
| MEDLINE | ID: mdl-35565344
7.
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.
Artigo
em Inglês
| MEDLINE | ID: mdl-35743737
8.
A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification.
PLoS One
; 17(9): e0274691, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36121822
9.
A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients.
Sci Rep
; 12(1): 7914, 2022 05 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-35552476
10.
Corrigendum: Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer.
Front Med (Lausanne)
; 9: 1089705, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36482915
11.
Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer.
Front Med (Lausanne)
; 9: 993395, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36213659
12.
Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.
Cancers (Basel)
; 13(2)2021 Jan 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-33477893
13.
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.
Artigo
em Inglês
| MEDLINE | ID: mdl-34268926
14.
Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs.
Sci Rep
; 11(1): 14123, 2021 07 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-34238968
15.
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.
Artigo
em Inglês
| MEDLINE | ID: mdl-34064923
16.
A Multicentre Evaluation of Dosiomics Features Reproducibility, Stability and Sensitivity.
Cancers (Basel)
; 13(15)2021 Jul 30.
Artigo
em Inglês
| MEDLINE | ID: mdl-34359737
17.
Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography Images.
Diagnostics (Basel)
; 11(4)2021 Apr 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-33920221
18.
A Clinical Decision Support System for Predicting Invasive Breast Cancer Recurrence: Preliminary Results.
Front Oncol
; 11: 576007, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-33777733
19.
Radiomic Analysis in Contrast-Enhanced Spectral Mammography for Predicting Breast Cancer Histological Outcome.
Diagnostics (Basel)
; 10(9)2020 Sep 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-32957690
20.
The 3D isodose structure-based method for clinical dose distributions comparison in pretreatment patient-QA.
Med Phys
; 46(2): 426-436, 2019 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-30450559