Emergency Medicine

Indirect visual guided fracture reduction robot based on external markers.

BACKGROUND: Traditional fracture reduction surgery cannot ensure the accuracy of the reduction while consuming the physical strength of the surgeon. Although monitoring the fracture reduction process through radiography can improve the accuracy of the reduction, it will bring radiation harm to both patients and surgeons.

Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.

BACKGROUND: A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in the emergency department (ED). Therefore, we conducted the present study to clarify it.

Artificial intelligence in trauma systems.

Local trauma care and regional trauma systems are data-rich environments that are amenable to machine learning, artificial intelligence, and big-data ...

PCR-detectable DNA exists a short period in the blood of systemic candidiasis murine model.

Invasive candidiasis is a major challenge to clinical medicine today. However, traditional fungal diagnostic techniques and empirical treatments have ...

Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning.

The triage of acute stroke patients is increasingly dependent on four-dimensional CTA (4D-CTA) imaging. In this work, we present a convolutional neura...

System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-Directed Clinical Evaluations During Radiation and Chemoradiation.

PURPOSE: Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation or ho...

Knowledge-Based Decision Support in Healthcare via Near Field Communication.

The benefits of automatic identification technologies in healthcare have been largely recognized. Nevertheless, unlocking their potential to support t...

Forty years of emergency medicine research: Uncovering research themes and trends through topic modeling.

STUDY OBJECTIVE: Topic identification can facilitate knowledge curation, discover thematic relationships, trends, and predict future direction. We aim...

Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.

Quantitative assessment of proliferation can be an important endpoint in toxicologic pathology. Traditionally, cell proliferation is quantified by lab...

A Study of Modified Infotaxis Algorithms in 2D and 3D Turbulent Environments.

Emergency response to hazardous gases in the environment is an important research field in environmental monitoring. In recent years, with the rapid d...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive type 1 diabetes mellitus (SPT1DM), whose insulin s...

Incessant Pericarditis With Recurrent Cardiac Tamponade as the Manifestation of Autoimmune Polyglandular Syndrome Type II.

A 23-year-old man was admitted for acute pericarditis that evolved to cardiac tamponade and shock with need of emergent pericardiocentesis and inotrop...

Point-of-Care Quantification of Serum Alpha-Fetoprotein for Screening Birth Defects in Resource-Limited Settings: Proof-of-Concept Study.

BACKGROUND: Maternal serum alpha-fetoprotein (MSAFP) concentration typically increases during pregnancy and is routinely measured during the second tr...

A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses.

OBJECTIVE: Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resource...

Automated classification of hip fractures using deep convolutional neural networks with orthopedic surgeon-level accuracy: ensemble decision-making with antero-posterior and lateral radiographs.

Background and purpose - Deep-learning approaches based on convolutional neural networks (CNNs) are gaining interest in the medical imaging field. We ...

Closed-loop machine-controlled CPR system optimises haemodynamics during prolonged CPR.

OBJECTIVES: We evaluated the feasibility of optimising coronary perfusion pressure (CPP) during cardiopulmonary resuscitation (CPR) with a closed-loop...

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before pr...

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.

As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine syst...

A Single-Center Evaluation of Extended Infusion Piperacillin/Tazobactam for Empiric Treatment in the Intensive Care Unit.

Piperacillin/tazobactam (PTZ) extended infusion (EI) is often used empirically in the intensive care unit (ICU). Gram-negative (GN) organisms with PT...

Artificial Intelligence Solutions for Analysis of X-ray Images.

Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care...