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Can machine learning unravel unsuspected, clinically import..:
Ninomiya, Kai
;
Kageyama, Shigetaka
;
Garg, Scot
...
European Heart Journal - Digital Health. 4 (2023) 3 - p. 275-278 , 2023
Link:
https://doi.org/10.1093/ehjdh/ztad014
RT Journal T1 <Title>Can machine learning unravel unsuspected, clinically important factors predictive of long-term mortality in complex coronary artery disease? A call for 'big data'</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1093_ehjdh_ztad014&Exemplar=1&LAN=DE A1 Ninomiya, Kai A1 Kageyama, Shigetaka A1 Garg, Scot A1 Masuda, Shinichiro A1 Kotoku, Nozomi A1 Revaiah, Pruthvi C A1 O'leary, Neil A1 Onuma, Yoshinobu A1 Serruys, Patrick W A1 for the SYNTAX Extended Survival Investigators PB Oxford University Press (OUP) YR 2023 SN 2634-3916 JF European Heart Journal - Digital Health VO 4 IS 3 SP 275 OP 278 LK http://dx.doi.org/https://doi.org/10.1093/ehjdh/ztad014 DO https://doi.org/10.1093/ehjdh/ztad014 SF ELIB - SuUB Bremen
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