Latest AI and machine learning research in emergency medicine for healthcare professionals.
Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty i...
Chest radiography is the modality of choice for the identification of rib fractures in young children and there is value for the development of computer-aided rib fracture detection in this age group. However, the automated identification of rib fractures on chest radiographs can be challenging due to the need for high spatial resolution in deep learning frameworks. A patch-based deep learning alg...
OBJETIVO: To describe the initial baseline results of a population-based study, as well as a protocol in order to evaluate the performance of differen...
BACKGROUND: Artificial intelligence applications have gained traction in the field of cerebrovascular disease by assisting in the triage, classificati...
The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artifici...
Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions....
OBJECTIVE: In this proof-of-concept study, we aimed to develop deep-learning-based classifiers to identify rib fractures on frontal chest radiographs ...
Cannulated screw fixation is the main therapy for femoral neck fractures, especially in young patients. The traditional surgical procedure uses C-arm ...
BACKGROUND: There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions o...
In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head...
PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital compli...
OBJECTIVE: Perilunate injuries are rare but devastating carpal injuries. The treatment of perilunate injuries remains challenging and contentious. Thi...
BACKGROUND: Whether primary brainstem hemorrhage (PBH) should be treated with a conservative treatment or with surgical intervention (such as cranioto...
IMPORTANCE: Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; howe...
Convolutional neural networks (CNNs) are widely used in the field of medical imaging diagnosis but have the disadvantages of slow training speed and l...
Susceptibility-weighted imaging (SWI) is a MR imaging technique suited to detect structural and microstructural abnormalities in traumatic brain injur...
BACKGROUND: Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically important in an ...
University emergency management ability is an important part of university safety management. To evaluate university emergency management ability scie...