Emergency Medicine

The association between cerebral small vessel disease and unfavorable hematoma morphology in primary intracerebral hemorrhage.

OBJECTIVE: To study the association between cerebral small vessel diseases (CSVD) and unfavorable hematoma morphology in primary intracerebral hemorrhage (ICH).

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the general population, significantly affecting morbidity and mortality. However, existing predictive models often lack sufficient accuracy and interpretability. We developed an interpretable and practical machine learning model to predict the risk of GIB in cardiology inpatients. This retrospective study ana...

Current state of AI for shockwave lithotripsy: a systematic review from YAU and EAU endourology.

PURPOSE: To consolidate the current evidence of artificial intelligence (AI) for management of nephrolithiasis using extracorporeal shock-wave lithotr...

Rapid trauma classification under data scarcity: an emergency on-scene decision model combining natural language processing and machine learning.

Trauma has become a major cause of increased morbidity and mortality worldwide. In emergency response, the classification of injuries is crucial as it...

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes.

Accurately predicting the severity of subarachnoid hemorrhage (SAH) is critical for informing clinical decisions and improving patient outcomes. This ...

Acute Management of Nasal Bone Fractures: A Systematic Review and Practice Management Guideline.

Nasal bone fractures represent the most common facial skeletal injury, challenging both function and aesthetics. This Preferred Reporting Items for Sy...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracerebral hemorrhage. We aimed to develop a risk assessm...

Human and animal models for studying hemorrhagic shock.

BACKGROUND: Studying the physiological response to severe hemorrhage remains challenging in real-world patients. Animal and human models mitigate some...

Humanizing AI training for health professions educators.

WHAT WAS THE EDUCATIONAL CHALLENGE?: Health professions educators grapple with profound emotional burdens-technology-related distress, gnawing self-do...

Machine learning combined with the PMF model reveals the sources and driving factors of PAHs and Cl-PAHs in urban runoff.

Urban rainwater runoff is an important source of nonpoint source pollution due to its transport of diverse contaminants, including polycyclic aromatic...

Assessing the Accuracy of ChatGPT in Appropriately Triaging Common Postoperative Concerns Regarding Mohs Micrographic Surgery.

Artificial intelligence (AI) is increasingly integrated into health care, offering potential benefits in patient education, triage, and administrative...

A Meta-Analysis of the Diagnosis of Condylar and Mandibular Fractures Based on 3-dimensional Imaging and Artificial Intelligence.

This article aims to review the literature, study the current situation of using 3D images and artificial intelligence-assisted methods to improve the...

Application of Transformer Neural Networks for Data Cleaning in Emergency Room Logs: A Case Study from the Bordeaux University Hospital.

Emergency Rooms (ERs) are at the center of various optimization research due to the growing number of visits in recent decades. The accurate logging o...

Deep Learning-Enhanced Hand-Driven Spatial Encoding Microfluidics for Multiplexed Molecular Testing at Home.

The frequent global outbreaks of viral infectious diseases have significantly heightened the urgent demand for molecular testing at home. However, the...

Prediction of Internal Exposures after Virtual Oral Doses of Disparate Chemicals in Rats and Humans Using Simplified Physiologically Based Pharmacokinetic Models with Generated Input Parameters.

Toxicological evaluation of industrial chemicals with a broad range of chemical structures, for example, bioactive food components, toxic food-derived...

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in trauma-induced coagulopathy.

Despite advancements in trauma care, uncontrolled hemorrhage and trauma-induced coagulopathy (TIC) remain the leading causes of preventable deaths aft...

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and pers...

Mechanobiology-guided machine learning models for predicting long bone fracture healing across diverse scenarios.

BACKGROUND: Fracture healing is a complex, time-dependent process governed by biological and mechanical factors, including implant properties. While f...

Promising for patients or deeply disturbing? The ethical and legal aspects of deepfake therapy.

Deepfakes are hyper-realistic but fabricated videos created with the use of artificial intelligence. In the context of psychotherapy, the first studie...

Impact of a computed tomography-based artificial intelligence software on radiologists' workflow for detecting acute intracranial hemorrhage.

PURPOSE: To assess the impact of a commercially available computed tomography (CT)-based artificial intelligence (AI) software for detecting acute int...