Emergency Medicine

Ovicidal and toxicological effect of hydroalcoholic extracts of var splendens, Boiss and L. against spp.: In vitro study.

Nematodes of the Ancylostomidae family consist of important parasitic species. The control of such parasitosis represents an important challenge, given the constant high rate of reinfection of some hosts, among which the domestic dog, as well as the high environmental contamination. Another factor that can have a negative influence is the toxicity of the chemicals used for environmental decontamin...

Are Silver Nanoparticles Useful for Treating Second-Degree Burns? An Experimental Study in Rats.

In this work, the potential usefulness of silver nanoparticles (AgNPs) for treating burn wounds was examined. Second-degree burns were induced in male Wistar rats by touching the skin with a heated (70°C) metallic device for 10 s, after which the animals were randomly allocated to one of two groups: control (n=8, treated with sterile saline) and experimental (n=8, treated with AgNPs, 0.081 mg/mL...

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke (AIS) patients. The aim of this paper is to devel...

Evaluation of machine learning-driven automated Kleihauer-Betke counting: A method comparison study.

INTRODUCTION: The Kleihauer-Betke (KB) test is the diagnostic standard for the quantification of fetomaternal hemorrhage (FMH). Manual analysis of KB ...

The opportunities and challenges of machine learning in the acute care setting for precision prevention of posttraumatic stress sequelae.

Personalized medicine is among the most exciting innovations in recent clinical research, offering the opportunity for tailored screening and manageme...

Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study.

The rapid spread of COVID-19 has resulted in the shortage of medical resources, which necessitates accurate prognosis prediction to triage patients ef...

Analysis of 17 fentanyls in plasma and blood by UPLC-MS/MS with interpretation of findings in surgical and postmortem casework.

The opioid crisis is linked to an increased misuse of fentanyl as well as fentanyl analogs that originate from the illicit drug market. Much of our cu...

The niche of artificial intelligence in trauma and emergency medicine.

Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals.

BACKGROUND: Severe sepsis and septic shock are among the leading causes of death in the United States and sepsis remains one of the most expensive con...

Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification.

Background and purpose - Classification of ankle fractures is crucial for guiding treatment but advanced classifications such as the AO Foundation/Ort...

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity a...

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments.

Between January and October of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has infected more than 34 million persons ...

Prediction of severe chest injury using natural language processing from the electronic health record.

INTRODUCTION: Trauma injury severity scores are currently calculated retrospectively from the electronic health record (EHR) using manual annotation b...

Decision-making in pediatric blunt solid organ injury: A deep learning approach to predict massive transfusion, need for operative management, and mortality risk.

BACKGROUND: The principal triggers for intervention in the setting of pediatric blunt solid organ injury (BSOI) are declining hemoglobin values and he...

Hierarchical fracture classification of proximal femur X-Ray images using a multistage Deep Learning approach.

PURPOSE: Suspected fractures are among the most common reasons for patients to visit emergency departments and often can be difficult to detect and an...

Prediction of obstetrical and fetal complications using automated electronic health record data.

An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that coul...

Postoperative Blood Loss Including Hidden Blood Loss in Early and Late Surgery Using Percutaneous Pedicle Screws for Traumatic Thoracolumbar Fracture.

INTRODUCTION: Some reports revealed that hidden blood loss (HBL) during surgery for traumatic thoracolumbar fracture cannot be ignored, even when usin...

The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review.

BACKGROUND: The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversation...

Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.

BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as triage tests for pulmonary tuberculosis in resourc...

Traffic Crash Severity Prediction-A Synergy by Hybrid Principal Component Analysis and Machine Learning Models.

The accurate prediction of road traffic crash (RTC) severity contributes to generating crucial information, which can be used to adopt appropriate mea...