Emergency Medicine

Machine-learning algorithms for detecting intracranial hemorrhage on head computed tomography.

This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: The primary objective of this review is to determine the diagnostic accuracy of any form of ML algorithm for detecting ICH in participants who underwent hCT. We will assess diagnostic accuracy by individual and pooled indicators such as sensitivity and specificity with 95% confidence intervals, positive and negat...

Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity.

Childhood obesity is a severe global epidemic, and emerging evidence suggests environmental pollutants like polystyrene microplastics (PS-MPs) may disrupt metabolic homoeostasis though mechanistic insights remain limited. This study integrated cross-species transcriptomics (from zebrafish and human adipose datasets), network toxicology, machine learning, and molecular docking to explore this link....

Diagnostic accuracy of deep learning vs. human raters for detecting osteoporotic vertebral compression fractures in routine CT scans.

OBJECTIVES: Vertebral fractures are severe complications of osteoporosis but are frequently missed on computed tomography (CT). Differentiating true f...

Artificial Intelligence and Public Health Data in Emergencies: A Critical Issue in the Middle East.

Timely access to reliable public health data is a critical determinant of effective response to health emergencies, including disease outbreaks, clima...

Machine learning guided resolution of mechanical trade-off in polymer composites via stress adaptive interface.

Developing polymer composites that simultaneously achieve high strength, toughness, and impact resistance remains a fundamental challenge due to inher...

Toxicogenomic Characterization of Perfluorooctanoic Acid-Associated Bladder Carcinogenesis.

OBJECTIVE: This study aims to bridge toxicological target prediction and bladder cancer transcriptomics by systematically identifying molecular signat...

Correction to: Developing a high-performance AI model for spontaneous intracerebral hemorrhage mortality prediction using machine learning in ICU settings.

Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks.

BACKGROUND: Real-world evaluation of large language models (LLMs) as clinical diagnostic aids is limited by the reliance on static vignettes and retro...

Comment on "Automatic rib fracture detection on postmortem CT data using deep learning".

Environmental PET-microplastic exposure and risk of non-alcoholic fatty liver disease: An integrated computational toxicology and multi-omics study.

The escalating severity of global microplastic pollution has triggered significant public health concerns. Polyethylene terephthalate (PET), a ubiquit...

A systematic review on dysconnectivity in face and emotion processing networks in schizophrenia.

Schizophrenia is a complex psychiatric disorder that affects approximately 20 million people worldwide. Patients show face-processing deficits that si...

Two -stage contrastive learning framework for vertebral compression fracture screening in frontal chest X-ray.

Vertebral Compression Fractures (VCFs) are early signs of osteoporosis and the most common type of osteoporotic fracture. In clinical practice, the pi...

A machine learning-based triage system for systemic EBV-positive T/NK cell lymphoproliferative diseases of childhood.

Systemic Epstein-Barr virus-positive (EBV-positive) T/NK cell lymphoproliferative diseases of childhood (sEBV+T/NK-LPD) are a spectrum of rare disease...

Brain organoids in environmental neurotoxicology: applications, mechanisms, and future perspectives.

The advent of human induced pluripotent stem cell (hiPSC)-derived brain organoids represents a significant advance in environmental neurotoxicology, p...

Predicting Geriatric Rehabilitation Stays of ≤4 Weeks After Hip Fracture Surgery: Machine Learning Approach Using Physical Activity and Patient Data.

BACKGROUND: In 2022, over 18,000 patients aged ≥70 years were hospitalized in the Netherlands for a hip fracture, with 50% requiring geriatric rehabil...

ChatGPT Health performance in a structured test of triage recommendations.

ChatGPT Health launched in January 2026 as OpenAI's consumer health tool, reaching millions of users. Here, we conducted a structured stress test of t...

First-line risk stratification with machine learning models facilitates rapid triage for non-ST-elevation myocardial infarction.

Timely diagnosis of non-ST-elevation myocardial infarction (NSTEMI) remains challenging, as current protocols rely on serial high-sensitivity cardiac ...

Machine learning and metabolic signatures of drowning: A pathway to uncovering cause of death in aquatic environments.

The postmortem diagnosis of drowning is challenging due to the nonspecific and transient nature of classical autopsy findings. This study aimed to inv...

Performance of AI vs radiology residents in the detection of intracranial hemorrhage on emergency CT: a real-world analysis.

OBJECTIVE: To evaluate the performance of a commercial artificial intelligence (AI) software in detecting intracranial hemorrhage (ICH) in emergency s...

Towards three-dimensional discrete fracture network modeling using integrated multidimensional outcrop data.

Analogue outcrops can be a source of fracture information beyond the resolution of seismic and well profiles, providing geometric, topological, and ge...