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pro vyhledávání: '"McGowan, Daniel"'
Automation of medical image interpretation could alleviate bottlenecks in diagnostic workflows, and has become of particular interest in recent years due to advancements in natural language processing. Great strides have been made towards automated r
Externí odkaz:
http://arxiv.org/abs/2407.21638
Recent work has uncovered alarming disparities in the performance of machine learning models in healthcare. In this study, we explore whether such disparities are present in the UK Biobank fundus retinal images by training and evaluating a disease cl
Externí odkaz:
http://arxiv.org/abs/2408.02676
The 5-year survival rate of Head and Neck Cancer (HNC) has not improved over the past decade and one common cause of treatment failure is recurrence. In this paper, we built Cox proportional hazard (CoxPH) models that predict the recurrence free surv
Externí odkaz:
http://arxiv.org/abs/2402.18417
Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) combined with Computed Tomography (CT) scans are critical in oncology to the identification of solid tumours and the monitoring of their progression. However, precise and consistent lesion seg
Externí odkaz:
http://arxiv.org/abs/2309.13675
Segmentation of head and neck (H\&N) tumours and prediction of patient outcome are crucial for patient's disease diagnosis and treatment monitoring. Current developments of robust deep learning models are hindered by the lack of large multi-centre, m
Externí odkaz:
http://arxiv.org/abs/2111.03848
Akademický článek
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Akademický článek
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Autor:
McGowan, Daniel Robin
In this thesis, the kinetics of fluoromisonidazole (FMISO) uptake by lung tumours in patients with advanced stage non-small cell lung cancer (NSCLC) is analysed. The uptake data was extracted from dynamic positron emission tomography (PET) images col
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.728781
Autor:
Aide, Nicolas *, Lasnon, Charline, Desmonts, Cedric *, Armstrong, Ian S, Walker, Matthew D, McGowan, Daniel R
Publikováno v:
In Seminars in Nuclear Medicine May 2022 52(3):286-301
Autor:
McGowan, Daniel D.
Aminoacyl-tRNA synthetases (ARSs) are responsible for charging amino acids (aas) onto cognate tRNAs, which are then delivered to ribosomes to be incorporated into proteins. While this process is efficient, aminoacylation of noncognate aas can occur d
Externí odkaz:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1406035036