Emergency Medicine

Prediction of hospitalization and waiting time within 24 hours of emergency department patients with unstructured text data.

Overcrowding of emergency departments is a global concern, leading to numerous negative consequences. This study aimed to develop a useful and inexpensive tool derived from electronic medical records that supports clinical decision-making and can be easily utilized by emergency department physicians. We presented machine learning models that predicted the likelihood of hospitalizations within 24 h...

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its diagnostic performance. In this retrospective multicenter study, using midline sagittal T2-weighted image with fracture (± PLC injury), a training dat...

Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients.

INTRODUCTION: Accurately predicting patient outcomes is crucial for improving healthcare delivery, but large-scale risk prediction models are often de...

Should ChatGPT Have Some Applicability in the Management of Emergency Dental Care for Emigrant Adults and Children?

How to cite this article: Veseli E, Tovani-Palone MR, Veseli A, . Should ChatGPT Have Some Applicability in the Management of Emergency Dental Care fo...

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and posi...

Artificial intelligence in emergency medicine. A systematic literature review.

UNLABELLED: Motivation and objective: Emergency medicine is becoming a popular application area for artificial intelligence methods but remains less i...

Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions.

Hospitals use medical cyber-physical systems (MCPS) more often to give patients quality continuous care. MCPS isa life-critical, context-aware, networ...

The impact of human-AI collaboration types on consumer evaluation and usage intention: a perspective of responsibility attribution.

Despite the widespread availability of artificial intelligence (AI) products and services, consumer evaluations and adoption intentions have not met e...

Application possibilities of artificial intelligence in facial vascularized composite allotransplantation-a narrative review.

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surgery that represents a dogmatic shift in the surgic...

Impact of Endoscopic Surgery Versus Robot CAS-R-2 Assisted with Stereotactic Drainage on Prognosis of Basal Ganglia Hypertensive Intracerebral Hemorrhage.

OBJECTIVE: To evaluate the impact of endoscopic surgery (ES) versus robot CAS-R-2 assisted with stereotactic drainage on prognosis of basal ganglia hy...

Efficacy and Safety of Chinese Herbal Medicine in Patients with Acute Intracerebral Hemorrhage: Protocol for a Randomized Placebo-Controlled Double-Blinded Multicenter Trial.

INTRODUCTION: The popular traditional Chinese medicine (TCM) compound FYTF-919 (Zhong Feng Xing Nao prescription) may improve outcome from acute intra...

Surgical skill level classification model development using EEG and eye-gaze data and machine learning algorithms.

The aim of this study was to develop machine learning classification models using electroencephalogram (EEG) and eye-gaze features to predict the leve...

A Real-Time Automated Machine Learning Algorithm for Predicting Mortality in Trauma Patients: Survey Says it's Ready for Prime-Time.

BACKGROUND: Though artificial intelligence ("AI") has been increasingly applied to patient care, many of these predictive models are retrospective and...

Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease.

BACKGROUND: Cerebral microbleeds (CMBs) serve as neuroimaging biomarkers to assess risk of intracerebral hemorrhage and diagnose cerebral small vessel...

Anaphylactic Shock to Intravenous Indocyanine Green During a Robotic Right Colectomy.

Intravenous indocyanine green (IV ICG) is regarded as a safe immunofluorescence agent used to assess bowel perfusion prior to creating bowel anastomos...

Mangled extremity: limb salvage for reconstruction versus primary amputation.

PURPOSE OF REVIEW: While MESS has historically influenced limb salvage versus amputation decisions, its universal applicability remains uncertain. Wit...

[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].

The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, trauma, and COVID-19 include more than 150,000 blo...

A multimodal deep learning model for predicting severe hemorrhage in placenta previa.

Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads to risk stratification and optimum allocation of i...

Beyond ChatGPT: What does GPT-4 add to healthcare? The dawn of a new era.

Over the past few years, artificial intelligence (AI) has significantly improved healthcare. Once the stuff of science fiction, AI is now widely used,...

A 48-Year-Old Man With a Hip Fracture and Skin Rash: A Case Report.

BACKGROUND/OBJECTIVE: Patients with systemic mastocytosis are at high risk of developing osteoporosis and fractures. Herein, we report a case of hip f...