reference/35287827

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/35287827

Outgoing Links

Predicate	Object
contentType	English Abstract\|Journal Article
endingPage	695
issn	1671-7104
issueIdentifier	6
pageRange	691-695
publicationName	Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
startingPage	691
bibliographicCitation	Song X, Zhang X, Li J, Liang L, Yang Y, Li G, Bai S. [Automatic Delineation of Clinical Target Volume and Organ at Risk by Deep Learning for Prostate Cancer Adaptive Radiotherapy]. Zhongguo Yi Liao Qi Xie Za Zhi. 2022 Nov 30;46(6):691–5. doi: 10.3969/j.issn.1671-7104.2022.06.021. PMID: 36597401.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_788550b25e8b5082c989376a5789cac1 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f08b454497ae3bd7c68ffa56ef1a7647 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_80d2054433a00b49722040a4d35fa69a http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_7b3065c547bd4dc80fd3cfcd022811f7 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_15414702ede6b2aa67b3f226f2d9a351 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_c0eb79a7239222ad9789af6bbef433ed http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_645bd5c7c983695f685c121707d165d3
date	2022-11-30-04:00^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://doi.org/10.3969/j.issn.1671-7104.2022.06.021 https://pubmed.ncbi.nlm.nih.gov/36597401
isPartOf	http://rdf.ncbi.nlm.nih.gov/pubchem/journal/21052 https://portal.issn.org/resource/ISSN/1671-7104
language	Chinese
source	https://pubmed.ncbi.nlm.nih.gov/
title	[Automatic Delineation of Clinical Target Volume and Organ at Risk by Deep Learning for Prostate Cancer Adaptive Radiotherapy]
hasPrimarySubjectTerm	http://id.nlm.nih.gov/mesh/D000077321 http://id.nlm.nih.gov/mesh/D011471Q000532 http://id.nlm.nih.gov/mesh/D011471Q000000981
hasSubjectTerm	http://id.nlm.nih.gov/mesh/D008297 http://id.nlm.nih.gov/mesh/D007091 http://id.nlm.nih.gov/mesh/D011880Q000379 http://id.nlm.nih.gov/mesh/D054893Q000379 http://id.nlm.nih.gov/mesh/D006801 http://id.nlm.nih.gov/mesh/D016571

Total number of triples: 32.