Xueping Jing
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Explore the profile of Xueping Jing including associated specialties, affiliations and a list of published articles.
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Articles
14
Citations
117
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0
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Recent Articles
1.
Zheng S, Cui X, Sun Y, Li J, Li H, Zhang Y, et al.
J Imaging Inform Med
. 2024 Jul;
38(1):422-438.
PMID: 38980627
Accurate image classification and retrieval are of importance for clinical diagnosis and treatment decision-making. The recent contrastive language-image pre-training (CLIP) model has shown remarkable proficiency in understanding natural images. Drawing...
2.
Jing X, Wielema M, Monroy-Gonzalez A, Stams T, Mahesh S, Oudkerk M, et al.
J Magn Reson Imaging
. 2023 Oct;
60(1):80-91.
PMID: 37846440
Background: Accurate breast density evaluation allows for more precise risk estimation but suffers from high inter-observer variability. Purpose: To evaluate the feasibility of reducing inter-observer variability of breast density assessment...
3.
Jing X, Dorrius M, Zheng S, Wielema M, Oudkerk M, Sijens P, et al.
Eur Radiol
. 2023 Sep;
34(3):2084-2092.
PMID: 37658141
Objectives: To develop a deep learning-based method for contrast-enhanced breast lesion detection in ultrafast screening MRI. Materials And Methods: A total of 837 breast MRI exams of 488 consecutive patients...
4.
Dong S, Jing X, Lin S, Lu K, Li W, Lu J, et al.
Environ Sci Technol
. 2022 Aug;
56(17):12179-12189.
PMID: 35947795
Uptake kinetics and delivery mechanisms of nanoparticles (NPs) in crop plants need to be urgently understood for the application of nanotechnology in agriculture as delivery systems for eco-friendly nanoagrochemicals. Here,...
5.
Jing X, Wielema M, Cornelissen L, van Gent M, Iwema W, Zheng S, et al.
Eur Radiol
. 2022 May;
32(12):8706-8715.
PMID: 35614363
Objectives: To investigate the feasibility of automatically identifying normal scans in ultrafast breast MRI with artificial intelligence (AI) to increase efficiency and reduce workload. Methods: In this retrospective analysis, 837...
6.
Jing X, Dorrius M, Wielema M, Sijens P, Oudkerk M, van Ooijen P
Cancers (Basel)
. 2022 Apr;
14(8).
PMID: 35454949
Purpose: To investigate the feasibility of using deep learning methods to differentiate benign from malignant breast lesions in ultrafast MRI with both temporal and spatial information. Methods: A total of...
7.
Zheng S, Cornelissen L, Cui X, Jing X, Veldhuis R, Oudkerk M, et al.
Med Phys
. 2020 Dec;
48(2):733-744.
PMID: 33300162
Purpose: Early detection of lung cancer is of importance since it can increase patients' chances of survival. To detect nodules accurately during screening, radiologists would commonly take the axial, coronal,...
8.
Lu K, Shen D, Liu X, Dong S, Jing X, Wu W, et al.
Chemosphere
. 2020 Jun;
259:127445.
PMID: 32593005
Iron oxide nanoparticles (nFeO)-filled materials have been widely employed in various products and their effects on plants have attracted considerable attention because of their potential release into the environment. Currently,...
9.
Ren J, Jing X, Wang J, Ren X, Xu Y, Yang Q, et al.
Laryngoscope
. 2020 Feb;
130(11):E686-E693.
PMID: 32068890
Objectives/hypothesis: To develop a deep-learning-based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design:...
10.
Dong S, Jing X, Cao Y, Xia E, Gao S, Mao L
Environ Pollut
. 2019 Jun;
252(Pt A):907-916.
PMID: 31226515
Immobilization of enzymes on carriers have been pursued to make the enzyme stable, reusable and obtaining even better enzyme activity. Due to the highly stable two-dimensional layer structure, large surface...