reference/21066047

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/21066047

Outgoing Links

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contentType	Journal Article\|Observational Study\|Research Support, Non-U.S. Gov't
issn	1471-2261
issueIdentifier	1
pageRange	33-
publicationName	BMC Cardiovascular Disorders
startingPage	33
hasFundingAgency	http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_487baf6554eb36bb22c6138d90a7c50f http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_1e6c02f7ca7cbf4d3bb3a2d331f34f29 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c1c4b2239c1fe2047bc2eb3481c88a0a
bibliographicCitation	Zhang J, Xu K, Hu Y, Yang L, Leng X, Jin H, Tang Y, Liu X, Ye C, Guo Y, Wang L, Zhang J, Feng Y, Mou C, Tang L, Xiang J, Du C. Diagnostic performance of deep learning and computational fluid dynamics-based instantaneous wave-free ratio derived from computed tomography angiography. BMC Cardiovascular Disorders. 2022 Feb 05;22(1):33. doi: 10.1186/s12872-022-02469-0.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_85703302b2c609f73d636c0e1b32c13a http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_881a0dbb2dead187da6521cda273f049 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_8aeea2b776ce32ba25c7d4a0f33dd45c http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_a818a3dcf163e1b9be174eb89ae83686 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_5a2aca2194602fbb09273c3d2cad5bc5 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_91284ca030ce998453e8b00f96719d86 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f0096e11f79007fa30e1cdc0f373e35f http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_de6688c627bb0114130b513cd52149fb http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_87343735100d5c83634ebca6eba8b263 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_1c220aaff117dcd404ec2963142d16b8 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f9ddf01832bea8dd4ce50b5fbe1da668 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f749cfdca0d90dd1b6d4e4932dc98ecc http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_64410f120bfaab57ce52af742a71b196 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_fd9c9db549000a69c7a2d221dddc36e2 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_7c56557cdfcef7018e17cc96172b4603 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_a3553a41bc66dc07379651a1e9d43d34 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_3ec5a5ac78098ea2cdb253971c6bd5dc
date	2022-02-05-04:00^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://pubmed.ncbi.nlm.nih.gov/35120463 https://doi.org/10.1186/s12872-022-02469-0 https://pubmed.ncbi.nlm.nih.gov/PMC8817609
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language	English
source	https://www.crossref.org/ https://scigraph.springernature.com/ https://pubmed.ncbi.nlm.nih.gov/
title	Diagnostic performance of deep learning and computational fluid dynamics-based instantaneous wave-free ratio derived from computed tomography angiography
discussesAsDerivedByTextMining	http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID10701 http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID8198

Total number of triples: 40.