Objective: To evaluate the effect of emergency medicine training credentials and years of medical experience on various clinical parameters in emergency medicine practice.
Methods: A cross-sectional study was conducted at Juntendo University Nerima Hospital between 1 April 2019 and 31 March 2020. All patients who were transported by ambulance, were examined by emergency physicians, and underwent computed tomography (CT) or magnetic resonance imaging (MRI) in the emergency department were included.
Aim: Senescent cells, inducing a senescence-associated secretory phenotype (SASP), lead to chronic inflammation in hard-to-heal wound tissue. However, eliminating senescent cells may impede normal wound healing due to their important role in the wound healing mechanism. Accordingly, we focused on wound exudates in hard-to-heal wounds, which contain many inflammation biomarkers consistent with SASP.
View Article and Find Full Text PDFBackground: Chat generative pre-trained transformer (ChatGPT) is a publicly available extensive artificial intelligence (AI) language model that leverages deep learning to generate text that mimics human conversations. In this study, the performance of ChatGPT was assessed by offering insightful and precise answers to a series of fictional questions and emulating a preliminary consultation on blepharoplasty.
Methods: ChatGPT was posed with questions derived from a blepharoplasty checklist provided by the American Society of Plastic Surgeons.
Background: During the COVID-19 pandemic, there was an increasing need to expand diagnostic testing in hospitals. At Keio University Hospital (KUH), clinical staff were concerned that the demand for PCR testing might exceed the capacity of the Clinical Laboratory. In response, basic researchers at Keio University School of Medicine (KUSM) set out to build a new, collaborative, PCR testing system.
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