Emergency Medicine

Survival prediction modeling for 1-year mortality in patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI).

BACKGROUND: ST elevation myocardial infarction (STEMI) is a life-threatening condition, and is associated with significant mortality, especially in patients encountering cardiogenic shock. Accurate risk assessment in this population is essential for improving prognosis through the early identification of patients at increased risk of adverse outcomes following successful revascularization. Our pre...

Elucidating the pathogenic mechanism underlying plasticizer-induced chronic kidney disease via integrated network toxicology and machine learning.

Plasticizers are ubiquitous plastic additives that have been linked to multiple adverse health outcomes and elevated risks of chronic kidney disease (CKD). However, the precise molecular mechanisms underlying plasticizer-induced CKD remain poorly understood. In this study, we screened five representative plasticizers and employed an integrated strategy of network toxicology and machine learning to...

Multicentre prospective cohort study to develop and validate a machine learning-based model for predicting 6-month all-cause mortality in elderly patients with advanced chronic obstructive pulmonary disease in China: study protocol.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) has an unpredictable clinical course, causing difficulties in short-term mortality predicti...

Artificial Intelligence in Neuroradiology: A Review of FDA-regulated Algorithms.

Artificial intelligence (AI) is increasingly integrated into neuroradiology practice, with a growing number of FDA-cleared algorithms now supporting t...

A translational IoT healthcare framework integrating secure sensing, energy-aware intelligence, and adaptive emergency response.

The Internet of Things (IoT) is transforming the healthcare industry by enabling real-time patient monitoring, predictive analytics and smart decision...

A machine learning system enables just-in-time risk-stratified sepsis evaluations in the neonatal intensive care unit.

INTRODUCTION: NICU sepsis evaluation balances rapid antibiotic administration for mortality reduction against unnecessary treatment. Objective risk st...

Comment on "integrating machine learning into fracture liaison services: Toward precision risk stratification in osteoporosis care".

Machine learning and deep learning for ankle fracture detection in radiographs: A systematic review with narrative synthesis on diagnostic performance and future clinical integration.

AIMS: Ankle fractures are a prevalent orthopedic injury with X-rays being the primary diagnostic tool. Errors in radiological interpretation leads to ...

Employing network toxicology, molecular docking, machine learning, and single-cell analysis to analyze BPA exposure-induced ccRCC.

This study investigates the molecular mechanisms underlying bisphenol A (BPA)-induced clear cell renal cell carcinoma (ccRCC). We integrated transcrip...

The Italian hand hygiene project: A joint-commission Italian network analysis.

BACKGROUND: Hand hygiene (HH) is a straightforward yet highly effective preventive measure against healthcare-associated infections; however, global c...

Feasibility and challenges of large language model (LLM)-generated neonatal resuscitation simulations: a multicenter exploratory study.

BACKGROUND: Simulation-based training (SBT) in neonatal resuscitation has positive impact on educational and neonatal outcomes. However, the implement...

Effects of peripheral nerve damage on promoting maladaptive plasticity in the spinal cord and brain.

Peripheral nerves can acquire damage through trauma, demyelinating diseases, inflammatory or immune-mediated insults, cancer, metabolic disorders, med...

[Clinical practice guidelines for the application of intelligent technology in spinal surgery (2026 edition)].

In response to the challenges of insufficient precision and limited safety associated with traditional techniques in the diagnosis and treatment of co...

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness.

A continuing challenge in aerospace materials is the search for alloys that have desired functional properties to operate at higher temperatures with ...

A narrative review of the role of AI and machine learning in enhancing cauda equina syndrome diagnosis.

INTRODUCTION: Cauda Equina Syndrome (CES) is a neurological emergency requiring rapid diagnosis. Traditional diagnostic methods face challenges due to...

External validity of deep learning solution for spontaneous intracranial hemorrhage detection on head CT scans.

We externally validated the performance of deep learning (DL) solution for detection of spontaneous intracerebral (ICH), intraventricular (IVH) and su...

Multi expert integrated algorithm for kidney biopsy triage.

Clinical decision-making often exhibits substantial inter-physician variability when evaluating identical patient data, limiting the reliability of co...

Predicting fire consequences with the transformer model based on multimodal feature fusion.

Accurate prediction of fire consequences is fundamental to process safety management and quantitative risk assessment in the chemical process industri...

Extended reality and emerging artificial intelligence in orthopedic surgical training: a scoping review of educational outcomes.

Immersive technologies have gained increasing relevance in orthopedic surgical education; however, the scope, outcomes, and maturity of extended reali...

Unveiling the role of air pollution in diabetic kidney disease: an integrated study combining network toxicology, machine learning, and Mendelian randomization.

Diabetic kidney disease (DKD) is a major and severe complication associated with diabetes. Air pollution is not only an independent risk factor for me...