Emergency Medicine

Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach.

Emergency departments (EDs) play a vital role in the whole healthcare system as they are the first p...

Human-mimetic soft robot joint for shock absorption through joint dislocation.

This paper presents a human-mimetic manipulator capable of shock absorption by using dislocation at ...

Machine Learning-Based Forecast of Hemorrhagic Stroke Healthcare Service Demand considering Air Pollution.

This study aimed to forecast the pattern of the demand for hemorrhagic stroke healthcare services ba...

A Gradient Boosting Machine Learning Model for Predicting Early Mortality in the Emergency Department Triage: Devising a Nine-Point Triage Score.

BACKGROUND: Emergency departments (ED) are becoming increasingly overwhelmed, increasing poor outcom...

Multivariate modeling of engineered nanomaterial features associated with developmental toxicity.

Despite the increasing prevalence of engineered nanomaterials (ENMs) in consumer products, their tox...

Increasing Cardiovascular Data Sampling Frequency and Referencing It to Baseline Improve Hemorrhage Detection.

UNLABELLED: We hypothesize that knowledge of a stable personalized baseline state and increased data...

Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology.

Toxicologic pathology is transitioning from analog to digital methods. This transition seems inevita...

Association between Blood Pressure after Haemodynamic Resuscitation in the Prehospital Setting and 28-Day Mortality in Septic Shock.

OBJECTIVE: Septic shock results in a decreased blood pressure (BP) leading to organ failure. The hae...

Machine learning for prediction of septic shock at initial triage in emergency department.

BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in...

Deep Learning for Chest Radiography in the Emergency Department.

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department.

BackgroundThe performance of a deep learning (DL) algorithm should be validated in actual clinical s...

Fixation of intracapsular fracture of the femoral neck using combined peripheral nerve blocks and transthoracic echocardiography in a patient with severe obstructive hypertrophic cardiomyopathy: a case report.

BACKGROUND: Hypertrophic obstructive cardiomyopathy (HOCM) is a type of hypertrophic cardiomyopathy ...

LiSep LSTM: A Machine Learning Algorithm for Early Detection of Septic Shock.

Sepsis is a major health concern with global estimates of 31.5 million cases per year. Case fatality...

Use of pressure-regulated volume control in the first 48 hours of hospitalization of mechanically ventilated patients with sepsis or septic shock, with or without ARDS.

PURPOSE: To evaluate the impact of pressure-regulated volume control (PRVC/VC+) use on delivered tid...

Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning.

Computed tomography (CT) of the head is used worldwide to diagnose neurologic emergencies. However, ...

Physicochemical stability of an admixture of lidocaine and ketamine in polypropylene syringe used in opioid-free anaesthesia.

OBJECTIVES: Opioid-free anaesthesia is a treatment strategy of pain management based on the use of d...

Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems.

Deep learning (DL) neural networks have only recently been employed to interpret chest radiography (...

Promoting head CT exams in the emergency department triage using a machine learning model.

PURPOSE: In this study, we aimed to develop a novel prediction model to identify patients in need of...

De novo Gastrinoma: A Case Report.

Gastrinomas are neuroendocrine tumors characterized by gastrin overexpression - 80% are sporadic and...

Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms.

BACKGROUND: Machine learning algorithms achieve expert-level accuracy in skin lesion classification ...

Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review.

BACKGROUND AND PURPOSE: Acute stroke caused by large vessel occlusions (LVOs) requires emergent dete...