Emergency medicine and its services have reached a breaking point during the COVID-19 pandemic. This pandemic has highlighted the failures of a system that needs to be reconsidered, and novel approaches need to be considered. Artificial intelligence (AI) has matured to the point where it is poised to fundamentally transform health care, and applications within the emergency field are particularly promising. In this viewpoint, we first attempt to depict the landscape of AI-based applications currently in use in the daily emergency field. We review the existing AI systems; their algorithms; and their derivation, validation, and impact studies. We also propose future directions and perspectives. Second, we examine the ethics and risk specificities of the use of AI in the emergency field.

The role of distractions on attentional lapses that place road users in higher risk of crash remains poorly understood. We aimed to assess the respective impact of (i) mind wandering trait (propensity to mind wander in the everyday life as measured with a set of 4 questions on the proportion of time spent mind wandering in 4 different situations) and (ii) mind wandering state (disturbing thoughts just before the crash) on road crash risk using a comparison between responsible and non-responsible drivers. 954 drivers injured in a road crash were interviewed at the adult emergency department of the Bordeaux university hospital in France (2013–2015). Responsibility for the crash, mind wandering (trait/state), external distraction, alcohol use, psychotropic drug use, and sleep deprivation were evaluated. Based on questionnaire reports, 39% of respondents were classified with a mind wandering trait and 13% reported a disturbing thought just before the crash. While strongly correlated, mind wandering state and trait were independently associated with responsibility for a traffic crash (State: OR = 2.51, 95% CI: 1.64–3.83 and Trait: OR = 1.62, 95% CI: 1.22–2.16 respectively). Self-report of distracting thoughts therefore did not capture the entire risk associated with the propensity of the mind to wander, either because of under-reported thoughts and/or other deleterious mechanisms to be further explored.

(1) Context: The management of acute coronary syndrome (ACS) is based on a rapid diagnosis. The aim of this study was to focus on the ACS symptoms differences according to gender, in order to contribute to the improvement of knowledge regarding the clinical presentation in women. (2) Methods: We searched for relevant literature in two electronic databases, and analyzed the symptom presentation for patients with suspected ACS. Fifteen prospective studies were included, with a total sample size of 10,730. (3) Results: During a suspected ACS, women present more dyspnea, arm pain, nausea and vomiting, fatigue, palpitations and pain at the shoulder than men, with RR (95%CI) of 1.13 [1.10; 1.17], 1.30 [1.05; 1.59], 1,40 [1.26; 1.56], 1.08 [1.01; 1.16], 1.67 [1.49; 1.86], 1.78 [1.02; 3.13], respectively. They are older by (95%CI) 4.15 [2.28; 6.03] years compared to men. The results are consistent in the analysis of the ACS confirmed subgroup. (4) Conclusions: We have shown that there is a gender-based symptomatic difference and a female presentation for ACS. The “typical” or “atypical” semiology of ACS symptoms should no longer be used.