2025
Detection of emergency department patients at risk of dementia through artificial intelligence
Cohen I, Taylor R, Xue H, Faustino I, Festa N, Brandt C, Gao E, Han L, Khasnavis S, Lai J, Mecca A, Sapre A, Young J, Zanchelli M, Hwang U. Detection of emergency department patients at risk of dementia through artificial intelligence. Alzheimer's & Dementia 2025, 21: e70334. PMID: 40457744, PMCID: PMC12130574, DOI: 10.1002/alz.70334.Peer-Reviewed Original ResearchConceptsElectronic health record dataHealth record dataEmergency departmentDetect dementiaDementia detectionYale New Haven HealthRecord dataRisk of dementiaEmergency department patientsBalance detection accuracyDementia algorithmsImprove patient outcomesCare coordinationCare transitionsDementia diagnosisReal-time applicationsClinical decision-makingClinician supportED usePatient safetyProbable dementiaMachine learning algorithmsED workflowED visitsED encounters
2024
Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions
Taylor R, Sangal R, Smith M, Haimovich A, Rodman A, Iscoe M, Pavuluri S, Rose C, Janke A, Wright D, Socrates V, Declan A. Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions. Academic Emergency Medicine 2024, 32: 327-339. PMID: 39676165, PMCID: PMC11921089, DOI: 10.1111/acem.15066.Peer-Reviewed Original ResearchClinical decision supportEmergency departmentArtificial intelligencePatient safetyDiagnostic errorsImplementing AIImprove patient safetyClinical decision support systemsEnhance patient outcomesReducing diagnostic errorsLeverage artificial intelligenceEmergency medicineHealth careTargeted educationReduce cognitive loadQuality improvementEmergency cliniciansData retrievalReal-time insightsDecision supportPatient outcomesCognitive overloadInformation-gathering processPatient detailsClinicians
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