Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry

scientific article published on 22 February 2020

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1161/JAHA.119.013958
P932PMC publication ID7335586
P698PubMed publication ID32089046

P50authorJames K. MinQ16213661
Filippo CademartiriQ35704469
Martin HadamitzkyQ39675009
Matthew J BudoffQ40403049
Pedro de Araújo GonçalvesQ45910878
Erica MaffeiQ51066788
Edoardo ConteQ53037434
Jagat NarulaQ56021238
Gianluca PontoneQ58875890
Hyuk-Jae ChangQ60161865
Kranthi K KolliQ61875684
Jonathon LeipsicQ63168795
Jeroen Joost BaxQ77085900
Byoung Kwon LeeQ81517967
Donghee HanQ86078084
Subhi J Al'ArefQ87783475
Fay Y LinQ87783477
Renu VirmaniQ88208229
Daniel S BermanQ89697826
Daniele AndreiniQ92118079
Gilbert L RaffQ92118097
Leslee J ShawQ94570815
Ilan GottliebQ96187000
Kavitha ChinnaiyanQ98148422
Heidi GransarQ106622987
Habib SamadyQ106720840
Alexander R van RosendaelQ114407025
Sangshoon ShinQ114407033
P2093author name stringPeter Stone
Yong-Jin Kim
Sang-Eun Lee
Jung Hyun Choi
Eun Ju Chun
Hugo Marques
Ji Min Sung
Lohendran Baskaran
P2860cites workDo plaques rapidly progress prior to myocardial infarction? The interplay between plaque vulnerability and progressionQ27023699
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P433issue5
P921main subjectcoronary artery diseaseQ844935
machine learningQ2539
P304page(s)e013958
P577publication date2020-02-22
P1433published inJournal of the American Heart Association: Cardiovascular and Cerebrovascular DiseaseQ19880670
P1476titleMachine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry
P478volume9