Detalhe da pesquisa
1.
Artificial Intelligence in Lung Cancer: Bridging the Gap Between Computational Power and Clinical Decision-Making.
Can Assoc Radiol J
; 72(1): 86-97, 2021 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-32735493
2.
Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging.
Can Assoc Radiol J
; 72(1): 73-85, 2021 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-32735452
3.
Bone Marrow and Tumor Radiomics at 18F-FDG PET/CT: Impact on Outcome Prediction in Non-Small Cell Lung Cancer.
Radiology
; 293(2): 451-459, 2019 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-31526257
4.
Predicting the need for a replan in oropharyngeal cancer: A radiomic, clinical, and dosimetric model.
Med Phys
; 51(5): 3510-3520, 2024 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-38100260
5.
Distinguishing recurrence from radiation-induced lung injury at the time of RECIST progressive disease on post-SABR CT scans using radiomics.
Sci Rep
; 14(1): 3758, 2024 02 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-38355768
6.
Distinguishing radiation fibrosis from tumour recurrence after stereotactic ablative radiotherapy (SABR) for lung cancer: a quantitative analysis of CT density changes.
Acta Oncol
; 52(5): 910-8, 2013 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-23106174
7.
External validation of a CT-based radiomics signature in oropharyngeal cancer: Assessing sources of variation.
Radiother Oncol
; 178: 109434, 2023 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-36464179
8.
Sarcopenia in head and neck cancer: A scoping review.
PLoS One
; 17(11): e0278135, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36441690
9.
Disparate participation by gender of conference attendants in scientific discussions.
PLoS One
; 17(1): e0262639, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-35061813
10.
Predicting recurrence risks in lung cancer patients using multimodal radiomics and random survival forests.
J Med Imaging (Bellingham)
; 9(6): 066001, 2022 Nov.
Artigo
em Inglês
| MEDLINE | ID: mdl-36388142
11.
Machine-Learning Approach to Differentiation of Benign and Malignant Peripheral Nerve Sheath Tumors: A Multicenter Study.
Neurosurgery
; 89(3): 509-517, 2021 08 16.
Artigo
em Inglês
| MEDLINE | ID: mdl-34131749
12.
MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.
Neurooncol Adv
; 3(1): vdab042, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-33977272
13.
Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features.
Tomography
; 6(2): 111-117, 2020 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-32548287
14.
Quantitative imaging feature pipeline: a web-based tool for utilizing, sharing, and building image-processing pipelines.
J Med Imaging (Bellingham)
; 7(4): 042803, 2020 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-32206688
15.
Machine and deep learning methods for radiomics.
Med Phys
; 47(5): e185-e202, 2020 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-32418336
16.
Modern treatment outcomes for early T-stage oropharyngeal cancer treated with intensity-modulated radiation therapy at a tertiary care institution.
Radiat Oncol
; 15(1): 261, 2020 Nov 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-33168055
17.
[18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non-Small Cell Lung Cancer.
Tomography
; 5(1): 145-153, 2019 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-30854452
18.
Pulmonary imaging after stereotactic radiotherapy-does RECIST still apply?
Br J Radiol
; 89(1065): 20160113, 2016 Sep.
Artigo
em Inglês
| MEDLINE | ID: mdl-27245137
19.
Detection of Local Cancer Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer: Physician Performance Versus Radiomic Assessment.
Int J Radiat Oncol Biol Phys
; 94(5): 1121-8, 2016 Apr 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-26907916
20.
Imaging texture analysis for automated prediction of lung cancer recurrence after stereotactic radiotherapy.
J Med Imaging (Bellingham)
; 2(4): 041010, 2015 Oct.
Artigo
em Inglês
| MEDLINE | ID: mdl-26835492