Emergency Medicine

Development and Validation of an Analytical Method to Quantitate Hydroxycitric Acid, the Key Constituent in Extract, in Rodent Plasma and Fetus.

extract (GCE) is a popular botanical supplement used in weight loss products. Hydroxycitric acid (HCA) is the principal component in GCE. Due to lack of adequate toxicity data to assess the safe use of GCE, the National Toxicology Program is testing GCE in Hsd:Sprague Dawley® SD® rats following perinatal exposure and in adult B6C3F1/N mice. We report a validated method utilizing sample clean up w...

Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation.

Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across health care facilities. We present a cross-facilities application of an AI model that predicts the need for an emergency caesarean during birth. The tran...

Validation of Analytical Method for Determination of Thallium in Rodent Plasma and Tissues by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS).

Thallium (Tl) can be released as a byproduct of smelting, mining, and other industries, causing human exposure. There are knowledge gaps on the toxici...

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.

Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase ...

Blood Pressure Model Based on Hybrid Feature Convolution Neural Network in Promoting Rehabilitation of Patients with Hypertensive Intracerebral Hemorrhage.

OBJECTIVE: Accurate prediction of the rise of blood pressure is essential for the hypertensive intracerebral hemorrhage. This study uses the hybrid fe...

Robotic donor hepatectomy: A major breakthrough in living donor liver transplantation.

Living donation in many countries is the main resource of organs. Healthy, volunteering individuals deserve the highest safety standards possible in a...

Machine Learning-Based HIV Risk Estimation Using Incidence Rate Ratios.

HIV/AIDS is an ongoing global pandemic, with an estimated 39 million infected worldwide. Early detection is anticipated to help improve outcomes and p...

RespiraTox - Development of a QSAR model to predict human respiratory irritants.

Respiratory irritation is an important human health endpoint in chemical risk assessment. There are two established modes of action of respiratory irr...

Research on Digital Economy of Intelligent Emergency Risk Avoidance in Sudden Financial Disasters Based on PSO-BPNN Algorithm.

In recent years, disasters have seriously affected the normal development of financial business in some regions. At the time of disaster, how to effec...

X-Ray Film under Artificial Intelligence Algorithm in the Evaluation for Nursing Effect of Gamma Nail Internal Fixation in Elderly Patients with Intertrochanteric Fracture of Femur.

The aim of this work was to explore the effects of Gamma nail internal fixation for intertrochanteric fracture of femur by X-ray film classification a...

Deep learning algorithm in detecting intracranial hemorrhages on emergency computed tomographies.

BACKGROUND: Highly accurate detection of intracranial hemorrhages (ICH) on head computed tomography (HCT) scans can prove challenging at high-volume c...

Deep learning-based image-analysis algorithm for classification and quantification of multiple histopathological lesions in rat liver.

Artificial intelligence (AI)-based image analysis is increasingly being used for preclinical safety-assessment studies in the pharmaceutical industry....

Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19.

A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and a...

Artificial intelligence to diagnosis distal radius fracture using biplane plain X-rays.

BACKGROUND: Although the automatic diagnosis of fractures using artificial intelligence (AI) has recently been reported to be more accurate than those...

Medical Information Mining-Based Visual Artificial Intelligence Emergency Nursing Management System.

This study aims to design a set of the visual artificial intelligence system based on medical information mining for hospital emergency care managemen...

Convolutional neural network performance compared to radiologists in detecting intracranial hemorrhage from brain computed tomography: A systematic review and meta-analysis.

PURPOSE: To compare the diagnostic accuracy of convolutional neural networks (CNN) with radiologists as the reference standard in the diagnosis of int...

Network analysis of trauma in patients with early-stage psychosis.

Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are...

The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. T...

Deep Learning-Based Detection and Diagnosis of Subarachnoid Hemorrhage.

Subarachnoid hemorrhage (SAH) is one of the critical and severe neurological diseases with high morbidity and mortality. Head computed tomography (CT)...

The Role of Machine Learning in Cardiovascular Pathology.

Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning t...