DeGrave AJ, Janizek JD, Lee S-I. Nat Mach Intell. 2021;3:610–619.
Artificial intelligence (AI) systems can support diagnostic decision-making. This study evaluates diagnostic “shortcuts” learned by AI systems in detecting COVID-19 in chest radiographs. Results reveal a need for better training data, improved choice in the prediction task, and external validation of the AI system prior to dissemination and implementations in different hospitals.
Stark N, Kerrissey M, Grade M, et al. West J Emerg Med. 2020;21:1095-1101.
This article describes the development and implementation of a digital tool to centralize and standardize COVID-19-related resources for use in the emergency department (ED). Clinician feedback suggests confirms that the tool has affected their management of COVID-19 patients. The tool was found to be easily adaptable to accommodate rapidly evolving guidance and enable organizational capacity for improvisation and resiliency.
Peyrony O, Marbeuf-Gueye C, Truong V, et al. Ann Emerg Med. 2020;76:405-412.
This prospective study enrolled all patients with suspected COVID-19 who were tested for SARS-CoV-2 in order to estimate the diagnostic accuracy of patients’ characteristics and emergency physician judgement in predicting COVID-19. Findings indicate that physician clinical judgement was generally accurate and that certain patient characteristics (loss of smell, lung ultrasound findings) increase the likelihood of identifying COVID-19.
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