Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease
Oikonomou EK, Siddique M, Antoniades C. Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease. Cardiovascular Research 2020, 116: 2040-2054. PMID: 32090243, PMCID: PMC7585409, DOI: 10.1093/cvr/cvaa021.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsBig DataCardiovascular DiseasesClinical Decision-MakingDiagnosis, Computer-AssistedHumansMachine LearningPhenotypePredictive Value of TestsPrognosisRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsTomography, X-Ray ComputedConceptsCardiac computed tomographyNon-invasive imagingCardiovascular imagingCardiovascular diseaseNon-invasive cardiovascular imagingCardiac CTCardiovascular risk stratificationFirst-line optionImportant clinical implicationsRisk stratificationUnstable patientsClinical careComputed tomographyCurrent evidenceClinical implicationsCardiac imagingRadiomics approachPatientsRadiomics methodTissue biologyCardiovascular diagnosticsDiseaseFuture studiesImagingPhenotyping