Nicholas Ng
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Explore the profile of Nicholas Ng including associated specialties, affiliations and a list of published articles.
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34
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919
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Recent Articles
1.
Ihdayhid A, Tzimas G, Peterson K, Ng N, Mirza S, Maehara A, et al.
Radiol Cardiothorac Imaging
. 2024 Nov;
6(6):e230312.
PMID: 39540820
Purpose To assess the diagnostic performance of a coronary CT angiography (CCTA) artificial intelligence (AI)-enabled tool (AI-QCPA; HeartFlow) to quantify plaque volume, as compared with intravascular US (IVUS). Materials and...
2.
Rinehart S, Raible S, Ng N, Mullen S, Huey W, Rogers C, et al.
J Soc Cardiovasc Angiogr Interv
. 2024 Aug;
3(3Part B):101296.
PMID: 39131216
Background: Artificial Intelligence Plaque Analysis (AI-QCPA, HeartFlow) provides, from a CCTA, quantitative plaque burden information including total plaque and plaque subtype volumes. We sought to evaluate the clinical utility of...
3.
Goswami A, Ng N, Yakubu E, Bassen G, Guchhait S
J Chem Phys
. 2024 Jun;
160(21).
PMID: 38828825
Single crystal Cr1.27Te2 samples were synthesized by using the chemical vapor transport method. Single crystal x-ray diffraction studies show a trigonal crystal structure with a P3̄m1 symmetry space group. We...
4.
Ng N, Foley D, Zhang X, Redemann B, Taheri M, McQueen T
Inorg Chem
. 2024 May;
63(21):9726-9734.
PMID: 38743495
A new misfit layered compound with the stoichiometry (EuS)(NbSe) (δ ≈ 0.13) has been successfully synthesized. High-resolution transmission electron microscopy and powder X-ray diffraction confirm the misfit structure with (EuS)-(EuS)...
5.
Narula J, Stuckey T, Nakazawa G, Ahmadi A, Matsumura M, Petersen K, et al.
Eur Heart J Cardiovasc Imaging
. 2024 May;
25(9):1287-1295.
PMID: 38700097
Aims: Coronary computed tomography angiography provides non-invasive assessment of coronary stenosis severity and flow impairment. Automated artificial intelligence (AI) analysis may assist in precise quantification and characterization of coronary atherosclerosis,...
6.
Kearns W, Stamoulis G, Glick J, Baisch L, Benner A, Brough D, et al.
J Mol Diagn
. 2024 Mar;
26(7):543-551.
PMID: 38556123
Applied artificial intelligence, particularly large language models, in biomedical research is accelerating, but effective discovery and validation requires a toolset without limitations or bias. On January 30, 2023, the National...
7.
Dundas J, Leipsic J, Fairbairn T, Ng N, Sussman V, Guez I, et al.
Circ Cardiovasc Imaging
. 2024 Mar;
17(3):e016143.
PMID: 38469689
Background: Luminal stenosis, computed tomography-derived fractional-flow reserve (FFR), and high-risk plaque features on coronary computed tomography angiography are all known to be associated with adverse clinical outcomes. The interactions between...
8.
Rymer J, Ng N, Takagi H, Koweek L, Douglas P, De Bruyne B, et al.
JACC Cardiovasc Imaging
. 2024 Mar;
17(6):705-707.
PMID: 38456878
No abstract available.
9.
Dundas J, Leipsic J, Sellers S, Blanke P, Miranda P, Ng N, et al.
Radiol Cardiothorac Imaging
. 2024 Jan;
5(6):e230124.
PMID: 38166336
Purpose To evaluate the performance of a new artificial intelligence (AI)-based tool by comparing the quantified stenosis severity at coronary CT angiography (CCTA) with a reference standard derived from invasive...
10.
Gabara L, Hinton J, Kira M, Saunders A, Shambrook J, Abbas A, et al.
J Cardiovasc Comput Tomogr
. 2023 Oct;
18(1):33-42.
PMID: 37872028
Background: A score combining the burden of stenosis severity on coronary computed tomography angiography (CCTA) and flow impairment by fractional flow reserve derived from computed tomography (FFR) may be a...