Emergency Medicine

Short-segment percutaneous fusion versus open posterior fusion with screw in the fractured vertebra for thoracolumbar junction burst vertebral fracture treatment.

OBJECTIVES: The treatment options for thoracolumbar junction burst fractures remain a topic of controversy. Short-segment percutaneous fixation (SSPF) and short-segment open fixation including the fractured level (SSOFIFL) are both viable procedures for managing these fractures. At present, there is a lack of evidence in the literature demonstrating the absolute superiority of one treatment over t...

Beyond SEP-1 Compliance: Assessing the Impact of Antibiotic Overtreatment and Fluid Overload in Suspected Septic Patients.

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) developed the Severe Sepsis and Septic Shock Performance Measure bundle (SEP-1) metric to improve sepsis care, but evidence supporting this bundle is limited and harms secondary to compliance have not been investigated.

Fully automated sinogram-based deep learning model for detection and classification of intracranial hemorrhage.

PURPOSE: To propose an automated approach for detecting and classifying Intracranial Hemorrhages (ICH) directly from sinograms using a deep learning f...

Improved patient mortality predictions in emergency departments with deep learning data-synthesis and ensemble models.

The triage process in emergency departments (EDs) relies on the subjective assessment of medical practitioners, making it unreliable in certain aspect...

Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data.

BACKGROUND: Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance,...

VenomPred 2.0: A Novel Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules.

The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug des...

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industr...

A Deep Learning Model for Automatic Segmentation of Intraparenchymal and Intraventricular Hemorrhage for Catheter Puncture Path Planning.

Intracerebral hemorrhage is the subtype of stroke with the highest mortality rate, especially when it also causes secondary intraventricular hemorrhag...

Machine Learning Algorithms to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis.

Delayed cerebral ischemia (DCI) is a common and severe complication after subarachnoid hemorrhage (SAH). Logistic regression (LR) is the primary metho...

Using Artificial Intelligence to Develop Educational Content for Teaching Children on Cardiopulmonary Resuscitation.

Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle.

In this study, we present a deep learning model for fracture classification on shoulder radiographs using a convolutional neural network (CNN). The pr...

Fully Automatic Dual-Probe Lung Ultrasound Scanning Robot for Screening Triage.

Two-dimensional lung ultrasound (LUS) has widely emerged as a rapid and noninvasive imaging tool for the detection and diagnosis of coronavirus diseas...

An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.

BACKGROUND: Within the trauma system, the emergency department (ED) is the hospital's first contact and is vital for allocating medical resources. How...

Identification of distinct clinical phenotypes of cardiogenic shock using machine learning consensus clustering approach.

BACKGROUND: Cardiogenic shock (CS) is a complex state with many underlying causes and associated outcomes. It is still difficult to differentiate betw...

Criticality and clinical department prediction of ED patients using machine learning based on heterogeneous medical data.

PROBLEM: Emergency triage faces multiple challenges, including limited medical resources and inadequate manual triage nurses, which cause incorrect tr...

Beyond the : Deep Learning Shows Promise in the Detection of Retinal Hemorrhage on Pediatric Head CT.

Automated fracture detection in the ulna and radius using deep learning on upper extremity radiographs.

OBJECTIVES: This study aimed to detect single or multiple fractures in the ulna or radius using deep learning techniques fed on upper-extremity radiog...

Combined robot-assisted transabdominal and perineal approach to reconstruct the posterior urethral distracted defect due to pelvic fracture: A case report.

Deep learning-assisted identification and quantification of aneurysmal subarachnoid hemorrhage in non-contrast CT scans: Development and external validation of Hybrid 2D/3D UNet.

Accurate stroke assessment and consequent favorable clinical outcomes rely on the early identification and quantification of aneurysmal subarachnoid h...

A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies.

Drug toxicity prediction is an important step in ensuring patient safety during drug design studies. While traditional preclinical studies have histor...