Latest AI and machine learning research in emergency medicine for healthcare professionals.
Femur fractures due to traumatic forces often require surgical intervention. Such surgeries require alignment of the femur in the presence of large muscular forces up to 500 N. Currently, orthopedic surgeons perform this alignment manually before fixation, leading to extra soft tissue damage and inaccurate alignment. One of the limitations of femoral fracture surgery is the limited vision and two-...
Percutaneous coronary intervention (PCI) has gradually become the most common treatment of coronary artery disease (CAD) in clinical practice due to its advantages of small trauma and quick recovery. However, the availability of hospitals with cardiac catheterization facilities and trained interventionalists is extremely limited in remote and underdeveloped areas. Remote vascular robotic system ca...
According to the "Istituto Superiore di Sanita'" (ISS), hospital infections are the most frequent and serious complication of health care. This consti...
OBJECTIVES: To develop and evaluate a machine learning model for predicting patient with trauma mortality within the US emergency departments.
OBJECTIVE: To compare the effectiveness of robot assisted and C-arm assisted percutaneous kyphoplasty (PKP) in the treatment of single/double-segment ...
OBJECTIVES: Validation of deep learning models should separately consider bedside chest radiographs (CXRs) as they are the most challenging to interpr...
OBJECTIVE: To explore the clinical application of Orthopedic Tianji Robot in the treatment of thoracolumbar fractures with minimally invasive percutan...
BACKGROUND: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose o...
BACKGROUND: Classic risk assessment tools often treat patients' risk factors as linear and additive. Clinical reality suggests that the presence of ce...
IMPORTANCE: Major life stressors, such as loss and trauma, increase the risk of depression. It is known that individuals show heterogeneous trajectori...
OBJECTIVE: The rapid onset of pediatric sepsis and the short optimal time for resuscitation pose a severe threat to children's health in the ICU. Time...
IMPORTANCE: Accurate prediction of adverse outcomes after acute myocardial infarction (AMI) can guide the triage of care services and shared decision-...
BACKGROUND: In-field triage tools for trauma patients are limited by availability of information, linear risk classification, and a lack of confidence...
A need exists to accurately estimate overdose risk and improve understanding of how to deliver treatments and interventions in people with opioid use ...
OBJECTIVE: Colorectal cancer (CRC) is the fourth most common cancer in UK. Symptomatic patients are referred via an urgent pathway and although most a...
To examine a new technique of robot-assisted nephroureterectomy without robot reldocking or patient repositioning. Patients diagnosed as upper tract...
To evaluate the rib fracture detection performance in computed tomography (CT) images using a software based on a deep convolutional neural network (D...
New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in p...
MOTIVATION: Many researchers with domain expertise are unable to easily apply machine learning (ML) to their bioinformatics data due to a lack of ML a...
BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality and poor neurologic outcomes. The biologic underpinnings of ...