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1.
Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment.
Eur Radiol
; 34(1): 279-286, 2024 Jan.
Artículo
en Inglés
| MEDLINE | ID: mdl-37572195
2.
Deep learning for standardized, MRI-based quantification of subcutaneous and subfascial tissue volume for patients with lipedema and lymphedema.
Eur Radiol
; 33(2): 884-892, 2023 Feb.
Artículo
en Inglés
| MEDLINE | ID: mdl-35976393
3.
Development of image-based decision support systems utilizing information extracted from radiological free-text report databases with text-based transformers.
Eur Radiol
; 2023 Nov 07.
Artículo
en Inglés
| MEDLINE | ID: mdl-37934243
4.
End-to-end automated body composition analyses with integrated quality control for opportunistic assessment of sarcopenia in CT.
Eur Radiol
; 32(5): 3142-3151, 2022 May.
Artículo
en Inglés
| MEDLINE | ID: mdl-34595539
5.
CT-derived Epicardial Adipose Tissue Inflammation Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement.
J Thorac Imaging
; 39(4): 224-231, 2024 Jul 01.
Artículo
en Inglés
| MEDLINE | ID: mdl-38389116
6.
Direct deep learning-based survival prediction from pre-interventional CT prior to transcatheter aortic valve replacement.
Eur J Radiol
; 168: 111150, 2023 Nov.
Artículo
en Inglés
| MEDLINE | ID: mdl-37844428
7.
Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy.
Insights Imaging
; 14(1): 1, 2023 Jan 05.
Artículo
en Inglés
| MEDLINE | ID: mdl-36600120
8.
Opportunistic CT-derived analysis of fat and muscle tissue composition predicts mortality in patients with cardiogenic shock.
Sci Rep
; 13(1): 22293, 2023 12 15.
Artículo
en Inglés
| MEDLINE | ID: mdl-38102168
9.
Deep Learning-Based Body Composition Analysis Predicts Outcome in Melanoma Patients Treated with Immune Checkpoint Inhibitors.
Diagnostics (Basel)
; 11(12)2021 Dec 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-34943551
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