http://rdf.ncbi.nlm.nih.gov/pubchem/reference/36621552

Outgoing Links

Predicate Object
contentType Journal Article
endingPage 190
issn 2666-6936
issueIdentifier 6
pageRange 183-190
publicationName Cardiovascular Digital Health Journal
startingPage 183
hasFundingAgency http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_47b82c0b9fd0c53483463fb1eb08a678
http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_77e2488754b2b37f99f84e3d30d28ece
http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_e95a2e29a39680e262b4b51ff9cf867f
http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_448c3d7a8b95445db230c0de0b6d375a
http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c69712507d6930bd0f8c8df12aeb228e
http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_eb4f340a1767b2ff28113b9d3c67834b
isSupportedBy http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_d28f4691748d297d44f5ef08def32d5d
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_c646d9324b501a57a6e5c5d481f6c5ea
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_b1a60a7f1fd6fc0306cb9e564c436faa
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_9df6568d8b8b4cf31a91ee14905b022d
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_93980e230f4aca29b4b3e1b4998bd267
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_f903f20a214dae7fb94db3bfd2e01eba
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_4c74ca5adb1338e1b388aae73be8d6cf
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_2df3e9231f8939f3d09f3190f5cec595
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_d8545d00b0005b17ffa5ec2961905c1b
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_f5462c9342a5b7075683084d7d6f7589
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_069f8d575ba3b90468c1cb688785f4cc
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_3c3ca4dfadd5a166a28e65f8aa5ef289
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_4b2184ea914170dbf511de92cbf2c87b
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_340e811d6a0669e5a068122f44b136c3
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_c87335cd43372c20a019f66f5f6d8834
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_3dda75fed3b6c8b49e7183db6374a0e2
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_c80836aa05d4e12ad05c7952e39ce2ad
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_f9bb0f8646d7e8319fbf45c76bab4b9e
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_7e7daeaa689549573c8d8c7dbbc8ce5a
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_c4a770725c07a745404f61ed986f6ea4
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_85572052608eace788febbbca07ff02c
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_8d06054b5d2dd71079955b27a73c8963
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_7c0ab371019b207f0f93c1d51607637b
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_81f72254510cb9a0ef8bc06e039ea1d0
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_e8edb0d1ec7853bb95e4d1ce7a363e02
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_2d1fc18b08f976f5a4cffd26f45e032f
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_a25f1709d6b5120ab0d057f0869304fb
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_713977bf89fc4fa4a1d9fe41f034afd7
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_f4f5ec55abf69b6779cec1644ccd8b53
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_8d7c6fb4fc32f59eaf2005ecc7350204
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_f43c638a270921c39f4885b8d508abad
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_7c975134a551ee6bb6b905a2107c4eb8
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_99efdd8bb3bb237dd9154ba1d1c23294
http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_71694f2dd88fbe11a989fc3c47cd45e5
bibliographicCitation Butler L, Karabayir I, Kitzman DW, Alonso A, Tison GH, Chen LY, Chang PP, Clifford G, Soliman EZ, Akbilgic O. A generalizable electrocardiogram-based artificial intelligence model for 10-year heart failure risk prediction. Cardiovascular Digital Health Journal. 2023 Dec;4(6):183–90. doi: 10.1016/j.cvdhj.2023.11.003.
creator http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0001-5632-8150
http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0001-5880-2282
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_e289de617f7242e99d1ae9ceeda47930
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_ceefaaf58a6301630575a767281aad6b
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_5581320512fb2dcacb481ce26bf61bf3
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_00870d832dd959da187e032eb50dba41
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_9da1733c952470f6a07382c98c69c69b
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_2b83d8c4319cfe8350582d3c151f1c79
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_ff463abe29ed1b2fa7700a57347ffda3
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_568a9014d509bebfbac1b077f52820a9
date 202312
identifier https://doi.org/10.1016/j.cvdhj.2023.11.003
https://pubmed.ncbi.nlm.nih.gov/38222101
https://pubmed.ncbi.nlm.nih.gov/PMC10787146
isPartOf http://rdf.ncbi.nlm.nih.gov/pubchem/journal/49956
https://portal.issn.org/resource/ISSN/2666-6936
language English
source https://www.crossref.org/
https://pubmed.ncbi.nlm.nih.gov/
title A generalizable electrocardiogram-based artificial intelligence model for 10-year heart failure risk prediction

Total number of triples: 68.