Emergency Medicine

Study protocol for a randomised controlled trial of humanoid robot-based distraction for venipuncture pain in children.

INTRODUCTION: Intravenous insertion (IVI) is a very common procedure in the emergency department (ED). IVI is often painful and stressful for both children and their families. Currently, distraction therapy is not used as a standard of care for IVI in North America. We propose that interaction with a humanoid robot may effectively distract children during IVI thereby reducing their pain and distre...

Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage.

There is a disparity between the increasing application of digital retinal imaging to neonatal ocular screening and slowly growing number of pediatric ophthalmologists. Assistant tools that can automatically detect ocular disorders may be needed. In present study, we develop a deep convolutional neural network (DCNN) for automated classification and grading of retinal hemorrhage. We used 48,996 di...

Effect of potential probiotic Leuconostoc mesenteroides FB111 in prevention of cholesterol absorption by modulating NPC1L1/PPARα/SREBP-2 pathways in epithelial Caco-2 cells.

Mustard kimchi consumption reduces cholesterol levels in rats. To identify lactic acid bacteria (LAB) in kimchi which exert this effect, 20 LAB isolat...

An Accurate Assessment of Docosahexaenoic Acid in Laying Hen Serum for Regulatory Studies.

Diets rich in omega-3 fatty acids (n-3 FA) have been associated with several health benefits. With the increased interest in n-3 FA both scientificall...

Defining Massive Transfusion in Civilian Pediatric Trauma With Traumatic Brain Injury.

The purpose of this study was to identify an optimal definition of massive transfusion in civilian pediatric trauma with severe traumatic brain injury...

Neurofuzzy c-Means Network-Based SCARA Robot for Head Gimbal Assembly (HGA) Circuit Inspection.

Decision and control of SCARA robot in HGA (head gimbal assembly) inspection line is a very challenge issue in hard disk drive (HDD) manufacturing. Th...

Robot-assisted intravertebral augmentation corrects local kyphosis more effectively than a conventional fluoroscopy-guided technique.

OBJECTIVEIntravertebral augmentation (IVA) is a reliable minimally invasive technique for treating Magerl type A vertebral body fractures. However, po...

Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study.

BACKGROUND: Resuscitated cardiac arrest is associated with high mortality; however, the ability to estimate risk of adverse outcomes using existing il...

A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation.

We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients followi...

A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospi...

Robot assisted minimally invasive esophagectomy (RAMIE) for esophageal cancer.

Worldwide, the standard treatment for locally advanced esophageal cancer with curative intent is perioperative chemotherapy or preoperative chemoradio...

A Unique Case of Severe Anemia Secondary to Copper Deficiency in an Adult Patient.

Anemia is a frequently encountered problem in the healthcare system. Common causes of anemia include blood loss, followed by impaired red blood cell p...

The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.

Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learnin...

The Healthy Children, Strong Families 2 (HCSF2) Randomized Controlled Trial Improved Healthy Behaviors in American Indian Families with Young Children.

BACKGROUND: American Indian (AI) families experience a disproportionate risk of obesity due to a number of complex reasons, including poverty, histori...

Supervised learning for bone shape and cortical thickness estimation from CT images for finite element analysis.

Knowledge about the thickness of the cortical bone is of high interest for fracture risk assessment. Most finite element model solutions overlook this...

A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation.

BACKGROUND: Cardiologs® has developed the first electrocardiogram (ECG) algorithm that uses a deep neural network (DNN) for full 12‑lead ECG analysis,...

Machine learning improves prediction of delayed cerebral ischemia in patients with subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) is a severe complication in patients with aneurysmal subarachnoid hemorrhage. Several associat...

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks.

Magnetic resonance imaging (MRI) has been proposed as a complimentary method to measure bone quality and assess fracture risk. However, manual segment...

Defining heatwave thresholds using an inductive machine learning approach.

Establishing appropriate heatwave thresholds is important in reducing adverse human health consequences as it enables a more effective heatwave warnin...