An ensemble model for predicting dispositions of emergency department patients.

Objective: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning's potential to predict ED dispositions, thus leading to promising substantial benefits. This study's objective is to create a predictive model for ED patient dispositions by employing ensemble learning.

The accuracy of artificial intelligence used for non-melanoma skin cancer diagnoses: a meta-analysis.

Background: With rising incidence of skin cancer and relatively increased mortality rates, an improved diagnosis of such a potentially fatal disease is of vital importance. Although frequently curable, it nevertheless places a considerable burden upon healthcare systems. Among the various types of skin cancers, non-melanoma skin cancer is most prevalent.

Impact of COVID-19 Pandemic on Emergency Department Volume and Acuity in Low Incidence Area: Taiwan's Experience in Three Hospitals.

Background: The decrease in emergency department (ED) patient visits during the COVID-19 pandemic was reported by various studies. Our study aimed to investigate whether a similar trend can be observed in a country with a low incidence of COVID-19 as well as the impact caused by the pandemic on ED patients in different triage levels and categories.

Methods: This multicenter retrospective study collected data from three regional hospitals between March 2019 and December 2020.

Effects of dietary Lactobacillus reuteri and Pediococcus acidilactici on the cultured water qualities, the growth and non-specific immune responses of Penaeus vannamei.

This study discussed the effects of two types of lactic acid bacteria, Lactobacillus reuteri (L. reuteri) and Pediococcus acidilactici (P. acidilactici), on the growth and nonspecific immunity of Penaeus vannamei (P.

The accuracy of machine learning approaches using non-image data for the prediction of COVID-19: A meta-analysis.

Objective: COVID-19 is a novel, severely contagious disease with enormous negative impact on humanity as well as the world economy. An expeditious, feasible tool for detecting COVID-19 remains yet elusive. Recently, there has been a surge of interest in applying machine learning techniques to predict COVID-19 using non-image data.

A modified cardiac triage strategy reduces door to ECG time in patients with ST elevation myocardial infarction.

Timely performing electrocardiography (ECG) is crucial for early detection of ST-elevation myocardial infarction (STEMI). For shortening door-to-ECG time, a chief complaint-based "cardiac triage" protocol comprising (1) raising alert among medical staff with bedside triage tags, and (2) immediate bedside ECG after focused history-taking was implemented at the emergency department (ED) in a single tertiary referral center. All patients diagnosed with STEMI visiting the ED between November 2017 and January 2020 were retrospectively reviewed to investigate the effectiveness of strategy before and after implantation.

Physician-related factors associated with unscheduled revisits to the emergency department and admission to the intensive care unit within 72 h.

Investigation of physician-related causes of unscheduled revisits to the emergency department (ED) within 72 h with subsequent admission to the intensive care unit (ICU) is an important parameter of emergency care quality. Between 2012 and 2017, medical records of all adult patients who visited the ED and returned within 72 h with subsequent ICU admission were retrospectively reviewed by three experienced emergency physicians. Study parameters were categorized into "input" (Patient characteristics), "throughput" (Time spent on first ED visit and seniority of emergency physicians, and "output" (Charlson Comorbidity Index).

The Effect of Processing Donor Milk on Its Nutrient and Energy Content.

The pasteurization is a mandatory step to inactivate pathogenic microorganisms of bank milk. For storage, freezing and thawing are necessary. The concentration of macronutrients and energy of bank milk could be influenced by these procedures which are routinely used in human milk bank.

Alternative Motor Task-Based Pattern Training With a Digital Mirror Therapy System Enhances Sensorimotor Signal Rhythms Post-stroke.

Mirror therapy (MT) facilitates motor learning and induces cortical reorganization and motor recovery from stroke. We applied the new digital mirror therapy (DMT) system to compare the cortical activation under the three visual feedback conditions: (1) no mirror visual feedback (NoMVF), (2) bilateral synchronized task-based mirror visual feedback training (BMVF), and (3) reciprocal task-based mirror visual feedback training (RMVF). During DMT, EEG recordings, including time-dependent event-related desynchronization (ERD) signal amplitude in both mu and beta bands, were obtained from the standard C3 (ispilesional hemisphere, IH), C4 (contralesional hemisphere, CH), and Cz scalp sites (supplementary motor area, SMA).

Low-intensity-ultrasound-accelerated nerve regeneration using cell-seeded poly(D,L-lactic acid-co-glycolic acid) conduits: an in vivo and in vitro study.

This study investigated the effects of low intensity ultrasound on seeded Schwann cells within poly(DL-lactic acid-co-glycolic acid) (PLGA) conduits by in vitro and in vivo trials for peripheral nerve regeneration. The possible differences in the ultrasonic effects when using biodegradable and non-biodegradable materials as the conduits were also studied, using silicone rubber tubes as comparisons. In the in vitro study, seeded Schwann cells were cultured in serum deprivation culture medium that simulated the environment of mechanical trauma on injury nerve site.