reference/34391226

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/34391226

Outgoing Links

Predicate	Object
contentType	Journal Article
issn	0920-1211
pageRange	107040-
publicationName	Epilepsy Research
startingPage	107040
bibliographicCitation	Zhao X, Jiang D, Hu Z, Yang J, Liang D, Yuan B, Lin R, Wang H, Liao J, Zhao C. Machine learning and statistic analysis to predict drug treatment outcome in pediatric epilepsy patients with tuberous sclerosis complex. Epilepsy Res. 2022 Dec;188():107040. doi: 10.1016/j.eplepsyres.2022.107040. PMID: 36332542.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f168f3396e69bad17890ca1b850139aa http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_a44a5ad500896d6f36ed7b0834079c62 http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0003-3341-4624 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_97dacca51308bfd7fe4f39acb397bb2e http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_54e7c8f73948f8c565f5efa76f7f4b33 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_1ce0d7623399652b3632b5003d9b7c19 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_8ae9db9fcaa1e5d23ce2df07febd64fa http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_036786c69ce7180298c38e96163bd147 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_c91ae18dadc964c28a9c50f6b01e9aff http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_7736ec0a74b47e1be91f83ea7b38edb3
date	202212
identifier	https://pubmed.ncbi.nlm.nih.gov/36332542 https://doi.org/10.1016/j.eplepsyres.2022.107040
isPartOf	http://rdf.ncbi.nlm.nih.gov/pubchem/journal/3587 https://portal.issn.org/resource/ISSN/0920-1211
language	English
source	https://www.crossref.org/ https://pubmed.ncbi.nlm.nih.gov/
title	Machine learning and statistic analysis to predict drug treatment outcome in pediatric epilepsy patients with tuberous sclerosis complex
hasPrimarySubjectTerm	http://id.nlm.nih.gov/mesh/D014402Q000150 http://id.nlm.nih.gov/mesh/D004827Q000209 http://id.nlm.nih.gov/mesh/D004827Q000188 http://id.nlm.nih.gov/mesh/D014402Q000188 http://id.nlm.nih.gov/mesh/D004827Q000000981 http://id.nlm.nih.gov/mesh/D014402Q000000981
hasSubjectTerm	http://id.nlm.nih.gov/mesh/D012189 http://id.nlm.nih.gov/mesh/D006801 http://id.nlm.nih.gov/mesh/D002648 http://id.nlm.nih.gov/mesh/D016896 http://id.nlm.nih.gov/mesh/D000069550
discussesAsDerivedByTextMining	http://rdf.ncbi.nlm.nih.gov/pubchem/gene/MD5_3c33894421ec07809347e7b0b7b19359 http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID7617 http://rdf.ncbi.nlm.nih.gov/pubchem/gene/MD5_646caaa7c99b02cebac462a51ebcdd71 http://rdf.ncbi.nlm.nih.gov/pubchem/gene/MD5_823fcecddb856aff97395f6263c49881 http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID9263 http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID9529 http://rdf.ncbi.nlm.nih.gov/pubchem/disease/DZID6522

Total number of triples: 43.