Machine learning algorithms estimating prognosis and guiding therapy in adult congenital heart disease: Data from a single tertiary centre including 10 019 patients

European Heart Journal

Volumn 40, Issue 13, 2019, Pages 1069-1077

  Diller, Gerhard Paul ^a,b,c,d   Kempny, Aleksander ^a,b   Babu Narayan, Sonya V ^a,b   Henrichs, Marthe ^c   Brida, Margarita ^a,e   Uebing, Anselm ^a,c   Lammers, Astrid E ^c   Baumgartner, Helmut ^c,d   Li, Wei ^a,b   Wort, Stephen J ^a,b   Dimopoulos, Konstantinos ^a,b   Gatzoulis, Michael A ^a,b  

^a ROYAL BROMPTON HOSPITAL   (United Kingdom)

^b NATIONAL HEART AND LUNG INSTITUTE   (United Kingdom)

^c UNIVERSITY HOSPITAL MÜNSTER   (Germany)

^d DZHK GERMAN CENTRE FOR CARDIOVASCULAR RESEARCH   (Germany)

^e KBC Zagreb   (Croatia)

Author keywords

Adult congenital heart disease; Deep learning; Machine learning; Mortality; Prognostication

Indexed keywords

ANGIOTENSIN RECEPTOR ANTAGONIST; ANTICOAGULANT AGENT; BETA ADRENERGIC RECEPTOR BLOCKING AGENT; BRAIN NATRIURETIC PEPTIDE; CREATININE; DIPEPTIDYL CARBOXYPEPTIDASE INHIBITOR;

ADULT; ALL CAUSE MORTALITY; ARTICLE; CARDIOPULMONARY EXERCISE TEST; COHORT ANALYSIS; CONGENITAL HEART DISEASE; DEEP LEARNING; DISEASE SEVERITY; ELECTROCARDIOGRAPHY; FEMALE; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MULTIDISCIPLINARY TEAM; NEW YORK HEART ASSOCIATION CLASS; PRIORITY JOURNAL; PROGNOSIS; PULMONARY HYPERTENSION; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; SURVIVAL PREDICTION; TERTIARY CARE CENTER; ALGORITHM; BLOOD; CLINICAL DECISION MAKING; CONGENITAL HEART MALFORMATION; EXERCISE TEST; FOLLOW UP; MIDDLE AGED; MORTALITY; PATHOPHYSIOLOGY; PATIENT CARE; PROCEDURES; SEVERITY OF ILLNESS INDEX;

ADULT; ALGORITHMS; CLINICAL DECISION-MAKING; DEEP LEARNING; ELECTROCARDIOGRAPHY; EXERCISE TEST; FOLLOW-UP STUDIES; HEART DEFECTS, CONGENITAL; HUMANS; HYPERTENSION, PULMONARY; MACHINE LEARNING; MIDDLE AGED; PATIENT CARE TEAM; PROGNOSIS; RETROSPECTIVE STUDIES; SEVERITY OF ILLNESS INDEX; TERTIARY CARE CENTERS;

EID: 85063994897     PISSN: 0195668X     EISSN: 15229645     Source Type: Journal    
DOI: 10.1093/eurheartj/ehy915     Document Type: Article

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