reference/35533230

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/35533230

Outgoing Links

Predicate	Object
contentType	Journal Article
endingPage	329
issn	1432-1084
issueIdentifier	1
pageRange	318-329
publicationName	European Radiology
startingPage	318
hasFundingAgency	http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_0bca3c32806f55af0a3eca5bb3b8eec7 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_4b69ad368086a6ca647d0f53274f61d5 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_7d9c6dd198194888f9a0cd4aa7248aa9 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_3d6327413f11e25da780fa61ff046bf4 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c1a758c3f295b7f901a647a50f38b0fd http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_066b879151477ef60bed9cc9f35d1b96 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_45b5493e57e756d758abc2ee521c3ac8 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_1bf6f1ba334654c4e78d86e12378d7a5 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_4a0f4db5fa8726d6c0437fc52c5e90a1 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_e019e18bca3de7168b7f251e8b7fef28
bibliographicCitation	Meng N, Feng P, Yu X, Wu Y, Fu F, Li Z, Luo Y, Tan H, Yuan J, Yang Y, Wang Z, Wang M. An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer. Eur Radiol. 2024 Jan;34(1):318–29. doi: 10.1007/s00330-023-09978-2. PMID: 37530809.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_0a8ef012cd2c9d19ac17de22c2399567 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_7df700a3a340626c7c6f2eb04c42cf05 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_9fc405d1221beff272e552ca6ace8e59 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_45223f429d618b3823cb954acccd2052 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_645bd5c7c983695f685c121707d165d3 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_6cc5eb17fe6c7f606703ebb6692bac80 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_59e8a9a06bf4740fa0e2abe1baebf9c3 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_40f66357d51ae17e376137a0f57d7571 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_db34d7277dd2968d072a9fcccedbc9ed http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_1ca1d8cd741fad553324fef32e3022b2 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_2bfa6053a9d9a233984f3b1850a4a5da http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_314c9c5ec17f5a69e3f9ae333596cdfb
date	2023-08-02-04:00^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://pubmed.ncbi.nlm.nih.gov/37530809 https://doi.org/10.1007/s00330-023-09978-2
isPartOf	http://rdf.ncbi.nlm.nih.gov/pubchem/journal/20371 https://portal.issn.org/resource/ISSN/1432-1084
language	English
source	https://pubmed.ncbi.nlm.nih.gov/ https://www.crossref.org/
title	An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer
discusses	http://id.nlm.nih.gov/mesh/M0029360
hasPrimarySubjectTerm	http://id.nlm.nih.gov/mesh/D008175Q000000981 http://id.nlm.nih.gov/mesh/D002289Q000000981 http://id.nlm.nih.gov/mesh/D002289Q000601
hasSubjectTerm	http://id.nlm.nih.gov/mesh/D000072078 http://id.nlm.nih.gov/mesh/D012189 http://id.nlm.nih.gov/mesh/D000097188 http://id.nlm.nih.gov/mesh/D006801 http://id.nlm.nih.gov/mesh/D019788 http://id.nlm.nih.gov/mesh/D000069550 http://id.nlm.nih.gov/mesh/D049268 http://id.nlm.nih.gov/mesh/D008279 http://id.nlm.nih.gov/mesh/D008198Q000000981
discussesAsDerivedByTextMining	http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID450503 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID68614 http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID7168 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID3232583 http://rdf.ncbi.nlm.nih.gov/pubchem/gene/MD5_bf22a1d0acfca4af517e1417a80e92d1 http://rdf.ncbi.nlm.nih.gov/pubchem/gene/MD5_a81b4e81fe71a07613c76a5538fe8b5e

Total number of triples: 58.