Publications by authors named "A M Shuster"

Background: While artificial intelligence has significantly impacted medicine, the application of large language models (LLMs) in oral and maxillofacial surgery (OMS) remains underexplored.

Purpose: This study aimed to measure and compare the accuracy of 4 leading LLMs on OMS board examination questions and to identify specific areas for improvement.

Study Design, Setting, And Sample: An in-silico cross-sectional study was conducted to evaluate 4 artificial intelligence chatbots on 714 OMS board examination questions.

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Beliefs have a powerful influence on our behavior, yet their neural mechanisms remain elusive. Here we investigate whether beliefs could impact brain activities in a way akin to pharmacological dose-dependent effects. Nicotine-dependent humans were told that nicotine strength in an electronic cigarette was either 'low', 'medium' or 'high', while nicotine content was held constant.

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Article Synopsis
  • The study aimed to compare the effectiveness of multidisciplinary coordinated care (CC) against traditional care (TC) for children with anterior uveitis, focusing on patient outcomes from 2013 to 2022.
  • Results showed that CC led to significantly better disease control, quicker initiation of biologic treatments, and lower corticosteroid use compared to TC, along with fewer clinic visits.
  • The study concluded that multidisciplinary care improved patient outcomes but noted limitations like variations in cohort start times and unclear referral criteria for CC.
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  • Most menstrual cycle studies have focused on small, lab-based samples of young women, limiting understanding of broader impacts across different ages and real-life conditions.
  • This study involved 116 healthy females, comprising young and midlife groups, using wearable tech to monitor finger temperature, heart rate, physical activity, and self-reported symptoms throughout the menstrual cycle.
  • Findings revealed that temperature fluctuated with the menstrual cycle phases, HR was lowest during menses for both groups, but sleep metrics remained stable regardless of cycle changes.
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The menstrual cycle is a loop involving the interplay of different organs and hormones, with the capacity to impact numerous physiological processes, including body temperature and heart rate, which in turn display menstrual rhythms. The advent of wearable devices that can continuously track physiological data opens the possibility of using these prolonged time series of skin temperature data to noninvasively detect the temperature variations that occur in ovulatory menstrual cycles. Here, we show that the menstrual skin temperature variation is better represented by a model of oscillation, the cosinor, than by a biphasic square wave model.

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