Scott J Lee
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Explore the profile of Scott J Lee including associated specialties, affiliations and a list of published articles.
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30
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747
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Recent Articles
1.
Zandehshahvar M, van Assen M, Kim E, Kiarashi Y, Keerthipati V, Tessarin G, et al.
J Imaging Inform Med
. 2024 Aug;
PMID: 39164451
In this study, we present a method based on Monte Carlo Dropout (MCD) as Bayesian neural network (BNN) approximation for confidence-aware severity classification of lung diseases in COVID-19 patients using...
2.
Ryce A, Lee S, Ahmed O, Majdalany B, Kokabi N
J Am Coll Radiol
. 2023 Dec;
21(5):712-720.
PMID: 38157951
Purpose: The aim of this study was to evaluate the relationship between prophylactic inferior vena cava filter (IVCF) implantation and in-hospital deep vein thrombosis (DVT), pulmonary embolism (PE), and mortality...
3.
Lee S, Fan S, Guo M, Majdalany B, Newsome J, Duszak Jr R, et al.
Clin Imaging
. 2022 Sep;
91:134-140.
PMID: 36087418
Purpose: To determine relationships between prophylactic inferior vena cava filter (IVCF) insertion and pulmonary embolism (PE), deep venous thrombosis (DVT), and in-hospital mortality outcomes in patients with severe traumatic pelvic/lower...
4.
van Assen M, Zandehshahvar M, Maleki H, Kiarashi Y, Arleo T, Stillman A, et al.
Br J Radiol
. 2022 Apr;
95(1134):20211028.
PMID: 35451863
Objective: The purpose was to evaluate reader variability between experienced and in-training radiologists of COVID-19 pneumonia severity on chest radiograph (CXR), and to create a multireader database suitable for AI...
5.
Monti C, van Assen M, Stillman A, Lee S, Hoelzer P, Fung G, et al.
Radiol Artif Intell
. 2022 Apr;
4(2):e210196.
PMID: 35391773
The purpose of this work was to assess the performance of a convolutional neural network (CNN) for automatic thoracic aortic measurements in a heterogeneous population. From June 2018 to May...
6.
Muscogiuri G, Ricci F, Scafuri S, Guglielmo M, Baggiano A, De Stasio V, et al.
J Thorac Imaging
. 2021 Sep;
37(1):2-16.
PMID: 34524203
Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of...
7.
van Assen M, Muscogiuri G, Caruso D, Lee S, Laghi A, De Cecco C
Radiol Med
. 2020 Sep;
125(11):1186-1199.
PMID: 32946002
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many...
8.
Pickhardt P, Graffy P, Zea R, Lee S, Liu J, Sandfort V, et al.
Lancet Digit Health
. 2020 Sep;
2(4):e192-e200.
PMID: 32864598
Background: Body CT scans are frequently performed for a wide variety of clinical indications, but potentially valuable biometric information typically goes unused. We investigated the prognostic ability of automated CT-based...
9.
Pickhardt P, Graffy P, Zea R, Lee S, Liu J, Sandfort V, et al.
Radiology
. 2020 Aug;
297(1):64-72.
PMID: 32780005
Background Body composition data from abdominal CT scans have the potential to opportunistically identify those at risk for future fracture. Purpose To apply automated bone, muscle, and fat tools to...
10.
Gordon S, Contreras-Moreira B, Levy J, Djamei A, Czedik-Eysenberg A, Tartaglio V, et al.
Nat Commun
. 2020 Jul;
11(1):3670.
PMID: 32728126
Our understanding of polyploid genome evolution is constrained because we cannot know the exact founders of a particular polyploid. To differentiate between founder effects and post polyploidization evolution, we use...