Emergency Medicine

Artificial intelligence meets point-of-care ultrasound: implications for pediatric emergency and critical care.

PURPOSE OF REVIEW: Artificial intelligence has been integrated in nearly all aspects of clinical care to improve patient outcomes, augment human capabilities and improve efficiency. Particularly in the field of radiology and medical imaging, artificial intelligence could revolutionize how care is delivered. In this review, we review the recent literature and provide an assessment of the advantages...

Mammalian AHR2 loss: Evolutionary patterns, mechanisms, and relevance of biological factors.

Environmental contamination by dioxins and polycyclic aromatic hydrocarbons threatens wildlife health, yet the molecular basis of interspecies variation in toxicological sensitivity remains poorly understood. The aryl hydrocarbon receptor (AHR) mediates dioxin-like responses and typically exists as two isoforms (AHR1 and AHR2) across vertebrates but mammals exhibit a unique evolutionary restructur...

Machine Learning Methods to Identify Pediatric Shunt Malfunction in the Acute Care Setting and the Development of ShuntGPT.

BACKGROUND AND OBJECTIVES: Identifying predictors of shunt failure in acute care settings is challenging. Previous studies largely rely on traditional...

Development and comparison of machine learning models for predicting postoperative ileus after posterior thoracolumbar fracture surgery.

In the artificial intelligence age, is Oswestry spinal risk index still useful? an external validation of Oswestry spinal risk index applied to radiotherapy patients and its relevance.

BACKGROUND AND STUDY AIMS: In 2013, Balain et al. proposed a scoring system, the Oswestry Spinal Risk Index (OSRI), to predict survival in patients wi...

Approach to Optimizing Tranexamic Acid Use in Trauma: Potential Utilization of Trauma Phenotypes.

Tranexamic acid (TXA) reduces mortality in patients with trauma; however, optimal patient selection remains unclear. This study aimed to identify trau...

Emerging Roles of Multiparametric Biodosimetry and Artificial Intelligence in Advancing Radiation Dose Assessment for Triage.

Biodosimetry plays a crucial role in radiation emergency preparedness and response by enabling efficient allocation of medical resources through prior...

Deep learning inversion of water content and relaxation time in water-bearing fracture zones based on surface NMR data.

Artificial intelligence for surgical care in war-torn sudan: Feasibility, barriers, and ethical perspectives from a conflict zone.

BACKGROUND: Artificial intelligence (AI) offers transformative potential for clinical care, yet its deployment in conflict-affected, low-resource sett...

Machine learning models for predicting delayed cerebral ischemia following ruptured intracranial aneurysms: A systematic review and meta-analysis.

BACKGROUND: Delayed cerebral ischemia (DCI) remains a major morbidity and mortality problem following aneurysmal subarachnoid hemorrhage (SAH). Advanc...

Early prediction of transfusion requirements in trauma patients using explainable machine learning.

INTRODUCTION: Hemorrhagic shock is the most common preventable cause of death in trauma patients. Early transfusion significantly improves survivabili...

Kaposi's sarcoma in individuals living with HIV: comparative assessment of AI-based clinical responses using a standardized questionnaire set.

OBJECTIVE: To comparatively evaluate the clinical responses of three digital platforms (ChatGPT 5.2, DeepSeek, Consensus) in terms of responsiveness, ...

Advancing DIA-Based Limited Proteolysis Workflows: Introducing DIA-LiPA.

Limited proteolysis coupled to mass spectrometry (LiP-MS) probes protein conformational dynamics, but interpretation of LiP-MS data is complicated by ...

Essence of toxicology research to Saudi Arabia Vision 2030 and beyond: Current state and future perspectives.

The Kingdom of Saudi Arabia has been making significant progress as part of its Vision 2030 to diversify its economy and reduce dependence on fossil f...

Artificial intelligence-assisted training for rib fracture interpretation: a prospective study in undergraduate medical students.

PURPOSE: Chest X-rays (CXRs) are essential in trauma care but have limited sensitivity for rib fracture detection, leading to frequent missed diagnose...

Enabling accurate chemical modeling of shocked energetic materials using a machine learning interatomic potential.

Understanding the complex chemistry of organic materials under dynamic compression is important for many applications, but it is challenging due to th...

Machine Learning and Computer Simulation Disentangle the Fuzzy Inhibitor Binding by Hsp90.

Heat shock protein 90 (Hsp90) is a key cancer drug target, yet the highly flexible N-terminal ATP-binding pocket yields seemingly conflicting crystall...

Microplastics on the frontline: causes, strategies to combat pollution and protect health with advanced bioremediation-a review.

Microplastic (MP) pollution is a growing global concern with serious implications for ecosystems and human health. The present review provides a compr...

Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.

BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and str...

Artificial Intelligence-Assisted Point-of-Care Ultrasound for Evaluating Left Ventricular Ejection Fraction: A Systematic Review of Prospective Observational Studies.

Artificial intelligence (AI) embedded in point-of-care ultrasound (POCUS) could reduce operator dependence in left ventricular ejection fraction (LVEF...