Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics
Purpose The aim of this systematic review was to analyse literature on artificial intelligence
(AI) and radiomics, including all medical imaging modalities, for oncological and non …
(AI) and radiomics, including all medical imaging modalities, for oncological and non …
Artificial intelligence: A critical review of applications for lung nodule and lung cancer
C de Margerie-Mellon, G Chassagnon - Diagnostic and Interventional …, 2023 - Elsevier
Artificial intelligence (AI) is a broad concept that usually refers to computer programs that
can learn from data and perform certain specific tasks. In the recent years, the growth of …
can learn from data and perform certain specific tasks. In the recent years, the growth of …
Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement
Objectives To evaluate radiomics studies according to radiomics quality score (RQS) and
Transparent Reporting of a multivariable prediction model for Individual Prognosis Or …
Transparent Reporting of a multivariable prediction model for Individual Prognosis Or …
Radiomics for survival risk stratification of clinical and pathologic stage IA pure-solid non–small cell lung cancer
Background Radiomics-based biomarkers enable the prognostication of resected non–small
cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA …
cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA …
CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer
Y Wang, W Liu, Y Yu, J Liu, H Xue, Y Qi, J Lei, J Yu… - European …, 2020 - Springer
Purpose To investigate the role of computed tomography (CT) radiomics for the preoperative
prediction of lymph node (LN) metastasis in gastric cancer. Materials and methods This …
prediction of lymph node (LN) metastasis in gastric cancer. Materials and methods This …
Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery
M Kirienko, L Cozzi, L Antunovic, L Lozza… - European journal of …, 2018 - Springer
Purpose Radiomic features derived from the texture analysis of different imaging modalities
e show promise in lesion characterisation, response prediction, and prognostication in lung …
e show promise in lesion characterisation, response prediction, and prognostication in lung …
A deep learning radiomics model for preoperative grading in meningioma
Objectives To noninvasively differentiate meningioma grades by deep learning radiomics
(DLR) model based on routine post-contrast MRI. Methods We enrolled 181 patients with …
(DLR) model based on routine post-contrast MRI. Methods We enrolled 181 patients with …
Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed …
P Yin, N Mao, C Zhao, J Wu, C Sun, L Chen, N Hong - European radiology, 2019 - Springer
Objective We aimed to identify optimal machine-learning methods for preoperative
differentiation of sacral chordoma (SC) and sacral giant cell tumour (SGCT) based on 3D …
differentiation of sacral chordoma (SC) and sacral giant cell tumour (SGCT) based on 3D …
Radiomics approach to prediction of occult mediastinal lymph node metastasis of lung adenocarcinoma
Y Zhong, M Yuan, T Zhang… - American Journal of …, 2018 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study was to evaluate the prognostic impact of radiomic
features from CT scans in predicting occult mediastinal lymph node (LN) metastasis of lung …
features from CT scans in predicting occult mediastinal lymph node (LN) metastasis of lung …
Differentiation of supratentorial single brain metastasis and glioblastoma by using peri-enhancing oedema region–derived radiomic features and multiple classifiers
F Dong, Q Li, B Jiang, X Zhu, Q Zeng, P Huang… - European …, 2020 - Springer
Objective To differentiate supratentorial single brain metastasis (MET) from glioblastoma
(GBM) by using radiomic features derived from the peri-enhancing oedema region and …
(GBM) by using radiomic features derived from the peri-enhancing oedema region and …