Publications by authors named "E A Olsen"

In order to relate nanoparticle properties to function, fast and detailed particle characterization is needed. The ability to characterize nanoparticle samples using optical microscopy techniques has drastically improved over the past few decades; consequently, there are now numerous microscopy methods available for detailed characterization of particles with nanometric size. However, there is currently no "one size fits all" solution to the problem of nanoparticle characterization.

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Background: Interest has recently increased in generative artificial intelligence (GenAI), a subset of artificial intelligence that can create new content. Although the publicly available GenAI tools are not specifically trained in the medical domain, they have demonstrated proficiency in a wide range of medical assessments. The future integration of GenAI in medicine remains unknown.

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Importance: Few studies have examined the extent to which employers emphasize financial over nonfinancial criteria in measurement, reporting, and decision-making about health care benefits.

Objective: To measure and identify factors associated with financial over nonfinancial emphasis in employer decision-making about health benefits.

Design, Setting, And Participants: A survey was administered to a nationally representative sample of US employers to assess the extent of employers' emphasis on benefits plans' costs over member experience, access to care, and equity, and on financial vs other considerations when choosing third-party benefits administrators.

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Influenza virus pandemics and seasonal epidemics have claimed countless lives. Recurrent zoonotic spillovers of influenza viruses with pandemic potential underscore the need for effective countermeasures. In this study, we show that pre-exposure prophylaxis with broadly neutralizing antibody (bnAb) MEDI8852 is highly effective in protecting cynomolgus macaques from severe disease caused by aerosolized highly pathogenic avian influenza H5N1 virus infection.

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Study Objectives: To update sleep medicine providers regarding (1) published research on the uses and performance of novel sleep tracking and testing technologies (2) the use of artificial intelligence to acquire and process sleep data and (3) research trends and gaps regarding the development and/or evaluation of these technologies.

Methods: Medline and Embase electronic databases were searched for studies utilizing screening and diagnostic sleep technologies, published between 2020 and 2022 in journals focusing on human sleep. Studies' quality was determined based on the Study Design criteria of The Oxford Centre for Evidence-Based Medicine Levels of Evidence.

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