Emergency Medicine

Development and validation of interpretable machine learning models to predict 30-day mortality in patients with intracerebral hemorrhage.

Intracerebral hemorrhage (ICH) carries high early mortality. To enable personalized decision-making, we developed and validated interpretable machine learning models for 30-day mortality prediction. This retrospective cohort study included patients with ICH extracted from the Medical Information Mart for Intensive Care (MIMIC) clinical database. Model development was performed using the MIMIC-IV (...

Prediction and mechanistic insights into drug-induced reproductive toxicity through integrated machine learning, FAERS-based signal comparison, and network toxicology analyses.

Drug-induced reproductive toxicity is a critical concern in drug safety evaluation, whereas conventional assessment methods are often constrained by high costs and long experimental cycles. In this study, a machine learning-based predictive model for reproductive toxicity was developed and integrated with data from the FDA Adverse Event Reporting System (FAERS), network toxicology analysis, molecu...

Skyer: a novel benchmark for evaluating the effectiveness of large language models in emergency department triage.

OBJECTIVES: Emergency department (ED) overcrowding causes diagnostic challenges, prolonged wait times, and impairs appropriate triage, often due to hu...

Unraveling Bone-Skin Crosstalk Enables miRNA Nanoformulation for Cutaneous Neurovascular Reconstruction in Diabetic Mice.

The clinical intractability of diabetic foot ulcers stems from a profound uncoupling of cutaneous neurovascular networks, rendering standard metabolic...

Integrating epigenetic and metabolic indicators for non-invasive endometrial cancer triage: a machine learning approach.

OBJECTIVE: Abnormal uterine bleeding (AUB) is a primary symptom indicative of endometrial cancer (EC), yet its diagnosis still primarily relies on inv...

Green radiology (part 1): environmental sustainability and energy consumption in medical imaging, with perspectives from Japan.

Climate change is an important public health challenge, and healthcare itself contributes to greenhouse gas emissions. Within healthcare, radiology is...

[Tele-emergency physicians-a cost-benefit analysis].

Telemedical applications are increasing-ranging from patients contacting a general practitioner to tele-emergency medicine and tele-intensive care for...

Artificial Intelligence for Evidence Synthesis of Emerging Biologics to Improve Skeletal Health in Osteogenesis Imperfecta: Systematic Review and Meta-Analysis.

BACKGROUND: Osteogenesis imperfecta (OI) is a rare genetic disorder characterized by bone fragility and recurrent fractures. Emerging biologics demons...

Predicting antenatal care dropout using machine learning and describing maternal and neonatal outcomes by dropout status in Sidama Region, Ethiopia: a retrospective cohort study.

OBJECTIVES: We aimed to develop and validate machine-learning models to predict antenatal care (ANC) dropout and describe maternal and neonatal outcom...

Simulation of covariate and concept drift in machine learning hospital admission prediction from emergency triage.

Machine learning models that predict hospital admission at triage may support patient flow forecasting, yet the effects of covariate drift, concept dr...

A robust, high-content NAM for repeatable and predictive developmental and reproductive toxicity assessment in C. elegans.

Developmental and reproductive toxicity (DART) assessment is essential for product safety evaluation but relies heavily on vertebrate models that are ...

Radiomics-based machine learning for splenic injury diagnosis using computed tomography (CT) images.

Efficient trauma assessment is essential for optimal patient care, with imaging playing a critical role in the detection of injuries. Rapid and accura...

Health system learning enables generalist neuroimaging models.

Frontier artificial intelligence (AI) models have advanced rapidly through training on internet-scale public data, yet such systems lack access to pri...

Evaluation of AI developed for rib fracture detection in identifying vertebral fractures on abdominal CT.

PURPOSE: To evaluate the performance of an AI algorithm originally developed for rib fracture detection in identifying vertebral fractures on abdomina...

The diagnostic accuracy of artificial intelligence in detecting foot and ankle fractures: a systematic review and meta-analysis of diagnostic test accuracy.

INTRODUCTION: Foot and ankle fractures, including radiographically subtle or occult injuries, present a diagnostic challenge in emergency settings, wi...

High temperature Nb-Si alloys using data science: optimization of fracture toughness and high-temperature strength.

High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m1/2) for processing ...

A 2004-2025 Bibliometric Study of Genetic Variation and Multiomics Biomarkers in Sepsis Based on 940 Publications.

Sepsis is a highly heterogeneous syndrome, and conventional clinical indicators and single biomarkers often fail to capture its biological complexity ...

Pepholin, a bacteriophage holin-derived antimicrobial peptide with membrane-disruptive activity and therapeutic efficacy in MDR Pseudomonas aeruginosa burn wounds.

The emergence of multidrug-resistant (MDR) Pseudomonas aeruginosa poses a serious threat to burn wound healing, necessitating the development of alter...

Decoding the role of phthalate plasticizers (DBP, DOP, and DEHP) in idiopathic pulmonary fibrosis: an integrated network toxicology and machine learning approach.

The molecular mechanism of idiopathic pulmonary fibrosis (IPF) caused by phthalate (PAE) is not well understood, presenting notable clinical and toxic...

Intelligent monitoring system for pipeline status based on MEMS acoustic emission sensors.

Pipeline structural health monitoring is critical for global energy security, yet traditional bulk piezoelectric acoustic emission (AE) sensors are in...