Detalhe da pesquisa
1.
Comprehensive Computed Tomography Radiomics Analysis of Lung Adenocarcinoma for Prognostication.
Oncologist;
23(7): 806-813, 2018 07.
Artigo
em Inglês
| MEDLINE
| ID: mdl-29622699
2.
Prognostic impact of nomogram based on whole tumour size, tumour disappearance ratio on CT and SUVmax on PET in lung adenocarcinoma.
Eur Radiol;
26(6): 1538-46, 2016 Jun.
Artigo
em Inglês
| MEDLINE
| ID: mdl-26455720
3.
Evaluation of early treatment response to radiotherapy for HCC using pre- and post-treatment MRI.
Acta Radiol;
60(7): 826-835, 2019 Jul.
Artigo
em Inglês
| MEDLINE
| ID: mdl-30282483
4.
Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography.
Korean J Radiol;
20(5): 749-758, 2019 05.
Artigo
em Inglês
| MEDLINE
| ID: mdl-30993926
5.
Imaging Phenotyping Using Radiomics to Predict Micropapillary Pattern within Lung Adenocarcinoma.
J Thorac Oncol;
12(4): 624-632, 2017 04.
Artigo
em Inglês
| MEDLINE
| ID: mdl-27923715
6.
Role of CT and PET Imaging in Predicting Tumor Recurrence and Survival in Patients with Lung Adenocarcinoma: A Comparison with the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society Classification of Lung Adenocarcinoma.
J Thorac Oncol;
10(12): 1785-94, 2015 Dec.
Artigo
em Inglês
| MEDLINE
| ID: mdl-26473646