Predictive artificial intelligence (AI) systems based on deep learning have been shown to achieve expert-level identification of diseases in multiple medical imaging settings, but can make errors in cases accurately diagnosed by clinicians and vice v...
Background: Hemorrhage remains the leading cause of death on the battlefield. This study aims to assess the ability of an artificial intelligence triage algorithm to automatically analyze vital-sign data and stratify hemorrhage risk in trauma patient...
Journal of the American College of Radiology : JACR
May 16, 2023
PURPOSE: To evaluate the real-world performance of two FDA-approved artificial intelligence (AI)-based computer-aided triage and notification (CADt) detection devices and compare them with the manufacturer-reported performance testing in the instruct...
PURPOSE: To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images.
OBJECTIVES: The aim of the study is to develop and evaluate the performance of a deep learning (DL) model to triage breast magnetic resonance imaging (MRI) findings in high-risk patients without missing any cancers.
Frontiers in cellular and infection microbiology
Mar 3, 2023
BACKGROUND: There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVI...
Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coronary syndrome (ACS), pulmonary embolism (PE), or aortic dissection (AD), often yielding negative resu...
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