Ralph T H Leijenaar
Overview
Explore the profile of Ralph T H Leijenaar including associated specialties, affiliations and a list of published articles.
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53
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8333
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Recent Articles
1.
Leijenaar R, Walsh S, Akshayaa Vaidyanathan , Aliboni L, Sanchez V, Leech M, et al.
Sci Rep
. 2023 May;
13(1):7198.
PMID: 37137947
The paper deals with the evaluation of the performance of an existing and previously validated CT based radiomic signature, developed in oropharyngeal cancer to predict human papillomavirus (HPV) status, in...
2.
Leech M, Leijenaar R, Hompland T, Gaffney J, Lyng H, Marignol L
Anticancer Res
. 2022 Dec;
43(1):351-357.
PMID: 36585179
Background/aim: Radiomics involves high throughput extraction of mineable precise quantitative imaging features that serve as non-invasive prognostic or predictive biomarkers. High levels of hypoxia are associated with a poorer prognosis...
3.
Muller M, Winz O, Gutsche R, Leijenaar R, Kocher M, Lerche C, et al.
J Neurooncol
. 2022 Jul;
159(3):519-529.
PMID: 35852737
Purpose: To investigate the potential of radiomics applied to static clinical PET data using the tracer O-(2-[F]fluoroethyl)-L-tyrosine (FET) to differentiate treatment-related changes (TRC) from tumor progression (TP) in patients with...
4.
Akshayaa Vaidyanathan , Guiot J, Zerka F, Belmans F, Van Peufflik I, Deprez L, et al.
ERJ Open Res
. 2022 May;
8(2).
PMID: 35509437
Purpose: In this study, we propose an artificial intelligence (AI) framework based on three-dimensional convolutional neural networks to classify computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19),...
5.
Zerka F, Urovi V, Bottari F, Leijenaar R, Walsh S, Gabrani-Juma H, et al.
Comput Biol Med
. 2021 Aug;
136:104716.
PMID: 34364262
Background: Artificial intelligence (AI) typically requires a significant amount of high-quality data to build reliable models, where gathering enough data within a single institution can be particularly challenging. In this...
6.
Guiot J, Akshayaa Vaidyanathan , Deprez L, Zerka F, Danthine D, Frix A, et al.
Med Res Rev
. 2021 Jul;
42(1):426-440.
PMID: 34309893
Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can...
7.
Keek S, Wesseling F, Woodruff H, van Timmeren J, Nauta I, Hoffmann T, et al.
Cancers (Basel)
. 2021 Jul;
13(13).
PMID: 34210048
Background: Locoregionally advanced head and neck squamous cell carcinoma (HNSCC) patients have high relapse and mortality rates. Imaging-based decision support may improve outcomes by optimising personalised treatment, and support patient...
8.
Frix A, Cousin F, Refaee T, Bottari F, Akshayaa Vaidyanathan , Desir C, et al.
J Pers Med
. 2021 Jul;
11(7).
PMID: 34202096
Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50 years. As modern medicine is evolving towards precision medicine, offering personalized patient care and treatment,...
9.
Ferreira M, Lovinfosse P, Hermesse J, Decuypere M, Rousseau C, Lucia F, et al.
Eur J Nucl Med Mol Imaging
. 2021 May;
48(11):3745-3746.
PMID: 34037832
No abstract available.
10.
Compter I, Verduin M, Shi Z, Woodruff H, Smeenk R, Rozema T, et al.
Radiother Oncol
. 2021 May;
160:132-139.
PMID: 33984349
Introduction: Glioblastoma (GBM) is the most common malignant primary brain tumour which has, despite extensive treatment, a median overall survival of 15 months. Radiomics is the high-throughput extraction of large...