2024
Trustworthy and ethical AI-enabled cardiovascular care: a rapid review
Mooghali M, Stroud A, Yoo D, Barry B, Grimshaw A, Ross J, Zhu X, Miller J. Trustworthy and ethical AI-enabled cardiovascular care: a rapid review. BMC Medical Informatics And Decision Making 2024, 24: 247. PMID: 39232725, PMCID: PMC11373417, DOI: 10.1186/s12911-024-02653-6.Peer-Reviewed Original ResearchConceptsHealthcare provider perspectiveRisk of patient harmCardiovascular careProvider perspectiveAI-based medical devicesPatient harmLoss of patient autonomyLack of robust evidenceTrust barriersHealthcare inequalitiesImprove careHealthcare providersCitation chasingPerceived lack of transparencyHealthcare existPatient careEthical concernsIntegration of AIPatient autonomyPatient interestLiterature reviewPerceived lackPractice guidelinesCareStudy design
2020
Prediction of outcomes after acute kidney injury in hospitalised patients: protocol for a systematic review
Arora T, Martin M, Grimshaw A, Mansour S, Wilson FP. Prediction of outcomes after acute kidney injury in hospitalised patients: protocol for a systematic review. BMJ Open 2020, 10: e042035. PMID: 33371041, PMCID: PMC7757434, DOI: 10.1136/bmjopen-2020-042035.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAdultArtificial IntelligenceHumansMeta-Analysis as TopicRenal DialysisSystematic Reviews as TopicConceptsAcute kidney injuryPrediction of outcomeSystematic reviewKidney injuryOutcomes of AKIResolution of AKIProgression of AKILong-term outcomesBias assessment toolRisk of biasMultivariable predictive modelMeta-Analyses (PRISMA) guidelinesPreferred Reporting ItemsFull-text reviewPrediction model RiskAKI careCohort studyNegative long-term outcomesThird reviewerReporting ItemsAbstract screeningComprehensive searchPatientsCommon diseaseData extraction