Emergency Medicine

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 pipeline of VCFs diagnosis consists of two examinations while most only routinely perform the first examination when the absence of clinical manifestations, leading to an underdiagnosis. In this study, we aim to explore the potential of VCFs screening ...

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 diseases that have highly variable biological behavior, from indolent conditions to highly aggressive malignancies. Clinicians currently face substantial challenges in promptly assessing disease severity and predicting patient outcomes, leading to limitatio...

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...

Development and validation of a machine learning-based nomogram model integrating LASSO regression and multiple evaluation methods for predicting early sepsis risk in acute abdomen.

BACKGROUND: Sepsis secondary to acute abdomen is a critical driver of clinical deterioration and mortality, with outcomes closely linked to sepsis sev...

Development and proof-of-concept of a treatment target recommendation algorithm in the context of cognitive processing therapy.

Background: Cognitive Processing Therapy (CPT) is an effective, widely supported treatment for PTSD, but patient response varies considerably. Optimal...

Reimagining intensive care unit recovery: The Critical Illness Survivorship Programme for humanising post-intensive care unit care - A discussion paper.

BACKGROUND: Survivorship after critical illness is often characterised by fragmented recovery and lingering cognitive, psychological, and physical imp...

Deciphering the air pollution-osteoarthritis relationship: insights from network toxicology, integrated machine learning, and molecular docking.

Mounting evidence suggests an association between air pollution and the pathogenesis of osteoarthritis (OA), yet the underlying molecular mechanisms r...

Multidimensional analysis of postoperative nursing challenges in oral cancer surgery: a retrospective study of 245 patients and proposal of the PROTECT mode.

PURPOSE: The quality of postoperative care for oral tumors critically influences patient prognosis and quality of life; however, current nursing syste...

Ensemble Machine Learning Models for Predicting Patients With High Usage: Model Validation and Economic Impact Analysis.

BACKGROUND: Machine learning models are increasingly used to predict patients at risk of high health care usage for targeted interventions. OBJECTIVE:...

Combining multimodal fatigue fracture surface images for analysis with a CNN.

This work uses three different modalities, namely SEM, BSE and scanning white light interference (SWLI) to image fatigue fracture surfaces of Ti-6Al-4...

Interpretable spatiotemporal machine learning reveals hydrogeological and climatic controls on groundwater heavy metal transport in acid mine drainage.

Acid mine drainage (AMD) generated by sulfide-bearing waste rock dumps poses persistent risks to groundwater through acidic leachate and heavy-metal m...

Exploring an Intermediate Colorectal Cancer Screening Test Based on Stool Proteomics and Machine Learning for Optimizing the Selection of Patients for Colonoscopy Identified from FIT.

The fecal immunochemical test (FIT) for detecting fecal occult blood, used alone or in combination with other stool biomarkers, has been demonstrated ...

Multi-level evidence reveals KCTD15 and FAM19A2 as key targets in PFOA/PFOS-mediated PCOS pathogenesis.

BACKGROUND: Polycystic ovary syndrome (PCOS), a common endocrine disorder, has been linked to environmental factors such as exposure to per- and polyf...

Automated Non-Invasive Burn Diagnostic System for Healthcare using Artificial Intelligence: AMBUSH-AI.

OBJECTIVE: Develop technology to predict burn wound depth using a combination of FDA approved ultrasound modalities and interpretation of these images...