Abirami Kirubarajan|Ahmed Taher|Shawn Khan|Sameer Masood
Artificial intelligence in emergency medicine: A scoping review
University of Toronto|University of Toronto|University of Toronto|University of Toronto|University Health Network|Toronto General Hospital
despite growing investment adoption artificial intelligence ai medicine applications ai emergency setting remain unclear scoping review seeks identify available literature regarding applications ai emergency medicinethe scoping review conducted according preferred reporting items systematic reviews metaanalyses prisma guidelines scoping reviews using medlineovid embase cinahl ieee double screening extraction process search included articles published february 28 2020 articles excluded selfclassify studying ai intervention relevant emergency department ed report outcomes evaluationof 1483 original database citations 395 eligible fulltext evaluation articles total 150 included scoping review majority included studies retrospective nature n 124 827 3 20 prospective controlled trials found 37 247 interventions aimed improving diagnosis within ed among 150 studies 19 127 focused diagnostic imaging within ed total 16 107 studies conducted outofhospital environment eg emergency medical services paramedics remainder occurring either ed trauma bay 24 16 studies human comparators 12 8 studies ai interventions outperformed clinicians least 1 measured outcomeairelated research rapidly increasing emergency medicine several promising ai interventions improve emergency care particularly acute radiographic imaging predictionbased diagnoses higher quality evidence needed assess short longterm clinical outcomes