Publications by authors named "YeongHo Choi"

Background: Injuries pose a significant global health challenge due to their high incidence and mortality rates. Although injury surveillance is essential for prevention, it is resource-intensive. This study aimed to develop and validate locally deployable large language models (LLMs) to extract core injury-related information from Emergency Department (ED) clinical notes.

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Colloidal quantum dot (QD)-based light-emitting diodes (QD-LEDs) have reached the pinnacle of quantum efficiency and are now being actively developed for next-generation displays and brighter light sources. Previous research has suggested utilizing inorganic hole-transport layers (HTLs) to explore brighter and more stable QD-LEDs. However, the performance metrics of such QD-LEDs with inorganic HTLs generally lag behind those of organic-inorganic hybrid QD-LEDs employing organic HTLs.

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Objective: To develop and externally validate models based on neural networks and natural language processing (NLP) to identify suspected serious infections in emergency department (ED) patients afebrile at initial presentation.

Methods: This retrospective study included adults who visited the ED afebrile at initial presentation. We developed four models based on artificial neural networks to identify suspected serious infection.

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Functionalization of quantum dots (QDs) via ligand exchange is prone to debase their photoluminescence quantum yield (PL QY) owing to the unavoidable surface damage by excess reactants, and even worse in aqueous medium. Herein, the oligomeric zinc thiolate as the multidentate hydrophilic ligand featuring facile synthetic protocol is proposed. A simple reaction between ZnCl and 3-mercaptopropionic acid produces oligomeric ligands containing 3-6 zinc thiolate units, where the terminal moieties provide multidentate anchoring to the surface as well as hydrophilicity.

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Objective: Motor vehicle collisions (MVCs) are known to cause traumatic cardiac arrest; it is unclear whether seat belts prevent this. This study aimed to evaluate the association between seat belt use and immediate cardiac arrest in cases of MVCs.

Method: This cross-sectional observational study used data from a nationwide EMS-based severe trauma registry in South Korea.

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Article Synopsis
  • The Korean out-of-hospital cardiac arrest registry (KOHCAR) was established in 2008 to monitor and improve survival rates for cardiac arrest cases outside of hospitals in South Korea.
  • KOHCAR gathers comprehensive data from emergency medical services and hospitals, allowing for a thorough analysis of patient care and outcomes.
  • While KOHCAR has positively impacted survival rates, the COVID-19 pandemic has created challenges that require better data use and communication strategies across various groups to improve outcomes going forward.*
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Article Synopsis
  • A study investigated the impact of extracorporeal cardiopulmonary resuscitation (ECPR) on neurological recovery for patients experiencing out-of-hospital cardiac arrest (OHCA).
  • Using data from a nationwide registry, researchers compared outcomes between 484 patients who received ECPR and a larger group of matched patients who did not.
  • Results showed that overall, ECPR was not linked to better neurological recovery, but early ECPR (within 45 minutes of arrival) did show a positive association with improved outcomes, indicating the need for further research on timing and implementation of ECPR.
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Heteroepitaxy on colloidal semiconductor nanocrystals is an essential strategy for manipulating their optoelectronic functionalities. However, their practical synthesis typically leads to scattered and unexpected outcomes due to the intervention of multiple reaction pathways associated with complicated side products of reactants. Here, the heteroepitaxy mechanism of zinc chalcogenide initiated on indium phosphide (InP) colloidal nanocrystals is elucidated using the precursors, zinc carboxylate and trialkylphosphine selenide.

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Objectives: Predicting diagnosis and prognosis of traumatic brain injury (TBI) at the prehospital stage is challenging; however, using comprehensive prehospital information and machine learning may improve the performance of the predictive model. We developed and tested predictive models for TBI that use machine learning algorithms using information that can be obtained in the prehospital stage.

Design: This was a multicentre retrospective study.

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High-resolution patterning of quantum dot (QD) films is one of the preconditions for the practical use of QD-based emissive display platforms. Recently, inkjet printing and transfer printing have been actively developed; however, high-resolution patterning is still limited owing to nozzle-clogging issues and coffee ring effects during the inkjet printing and kinetic parameters such as pickup and peeling speed during the transfer process. Consequently, employing direct optical lithography would be highly beneficial owing to its well-established process in the semiconductor industry; however, exposing the photoresist (PR) on top of the QD film deteriorates the QD film underneath.

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Background: In the emergency department (ED), adequate pain control is essential for managing patients; however, children with pain are known to receive less analgesia than adults with pain. We introduce the Pain Passport to improve pain management in paediatric patients with suspected fractures in the ED.

Methods: This was a before-and-after study.

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Background: Timely transfer and percutaneous coronary intervention (PCI) with or without thrombolysis are recommended by the American Heart Association (AHA) to care for ST-segment elevation myocardial infarction (STEMI) patients who present first to a non-PCI-capable hospital. This study was to evaluate the impact on in-hospital mortality of the compliance with guidelines regarding to the time of PCI for patients with STEMI who were transferred to a capable PCI hospital.

Methods: We used the CArdioVAscular disease Surveillance data from November 2007 to December 2012 for this study.

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