Emergency Medicine

Artificial intelligence chatbot performance in triage of ophthalmic conditions.

BACKGROUND: Timely access to human expertise for affordable and efficient triage of ophthalmic conditions is inconsistent. With recent advancements in publicly available artificial intelligence (AI) chatbots, the lay public may turn to these tools for triage of ophthalmic complaints. Validation studies are necessary to evaluate the performance of AI chatbots as triage tools and inform the public r...

Artificial intelligence in detecting dentomaxillofacial fractures in diagnostic imaging: a scoping review protocol.

INTRODUCTION: The dentomaxillofacial (DMF) area, which includes the teeth, maxilla, mandible, zygomaticum, orbits and midface, plays a crucial role in the maintenance of the physiological functions despite its susceptibility to fractures, which are mostly caused by mechanical trauma. As a diagnostic tool, radiographic imaging helps clinicians establish a diagnosis and determine a treatment plan; h...

Identification of Child Survivors of Sex Trafficking From Electronic Health Records: An Artificial Intelligence Guided Approach.

Survivors of child sex trafficking (SCST) experience high rates of adverse health outcomes. Amidst the duration of their victimization, survivors regu...

Real-time artificial intelligence system for bacteremia prediction in adult febrile emergency department patients.

BACKGROUND: Artificial intelligence (AI) holds significant potential to be a valuable tool in healthcare. However, its application for predicting bact...

Social Risk Factors are Associated with Risk for Hospitalization in Home Health Care: A Natural Language Processing Study.

OBJECTIVE: This study aimed to develop a natural language processing (NLP) system that identified social risk factors in home health care (HHC) clinic...

A Weakly Supervised Deep Learning Framework for Whole Slide Classification to Facilitate Digital Pathology in Animal Study.

The pathology of animal studies is crucial for toxicity evaluations and regulatory assessments, but the manual examination of slides by pathologists r...

Neural network for autonomous segmentation and volumetric assessment of clot and edema in acute and subacute intracerebral hemorrhages.

INTRODUCTION: Minimally-invasive surgical techniques for intracerebral hemorrhage (ICH) evacuation use imaging to guide the suction, lysing and/or dra...

Spatial attention-based residual network for human burn identification and classification.

Diagnosing burns in humans has become critical, as early identification can save lives. The manual process of burn diagnosis is time-consuming and com...

Quality of Layperson CPR Instructions From Artificial Intelligence Voice Assistants.

An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration.

Emergency department (ED) triage scale determines the priority of patient care and foretells the prognosis. However, the information retrieved from th...

Risk of Induction of Corneal Neovascularization with Topical Erythropoietin: An Animal Safety Study.

PURPOSE: To evaluate the pro-angiogenic effect of topical erythropoietin on cornea in chemical burn-injured rabbit eyes.

Feasibility of intra-operative image guidance in burn excision surgery with multispectral imaging and deep learning.

BACKGROUND: Exposing a healthy wound bed for skin grafting is an important step during burn surgery to ensure graft take and maintain good functional ...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively ...

Deep Learning for Localized Detection of Optic Disc Hemorrhages.

PURPOSE: To develop an automated deep learning system for detecting the presence and location of disc hemorrhages in optic disc photographs.

Mechanistic Task Groupings Enhance Multitask Deep Learning of Strain-Specific Ames Mutagenicity.

The Ames test is a gold standard mutagenicity assay that utilizes various strains with and without S9 fraction to provide insights into the mechanism...

Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms.

RATIONALE AND OBJECTIVES: Interpreting radiographs in emergency settings is stressful and a burden for radiologists. The main objective was to assess ...

Letter: Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success from Video.

Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression.

Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be effectively reduced by intervening on the risk facto...

Deep-Learning-Enabled Microwave-Induced Thermoacoustic Tomography Based on ResAttU-Net for Transcranial Brain Hemorrhage Detection.

OBJECTIVE: Hemorrhagic stroke is a leading threat to human's health. The fast-developing microwave-induced thermoacoustic tomography (MITAT) technique...

Identifying Differences in the Performance of Machine Learning Models for Off-Targets Trained on Publicly Available and Proprietary Data Sets.

Each year, publicly available databases are updated with new compounds from different research institutions. Positive experimental outcomes are more l...