Emergency Medicine

Agreement between three state-of-the-art deep learning bone age estimation models and chronological age in a large contemporary pediatric cohort.

BACKGROUND: Radiographic bone age estimation is routinely performed in children to evaluate short stature, early or late puberty, and endocrine disorders, as well as for surgical planning. OBJECTIVE: To evaluate agreement between three state-of-the-art deep learning bone age estimation models and chronological age in a large contemporary pediatric cohort. MATERIALS AND METHODS: We retrospectively ...

AI-Based Triage Decision Support: Multisite Economic Evaluation in the United States.

BACKGROUND: Emergency department (ED) visits have risen in the United States, with demand for emergency care exceeding supply. Resultant ED crowding harms patients, causes staff burnout, and places financial strain on hospitals, payers, and patients alike. Digital tools, including those leveraging artificial intelligence (AI), offer promise for driving efficiency and mitigating the harms of crowdi...

Artificial Intelligence-Mediated Teledentistry for Ageing Populations: Toward Intelligent Intermediary Support in Home-Based Oral Care.

The rapid ageing of the global population is reshaping oral health care delivery, with increasing numbers of older adults receiving care in home-based...

Deep learning-based automated assessment of pulmonary artery indices and surgical approach triage for tetralogy of Fallot from multicenter cardiac computed tomography (CT).

AIM: To develop an automated framework for deep learning (DL)-based segmentation, pulmonary artery indices (PAIs) computation, and rule-based surgical...

How machine learning applied on fMRI could improve the prognosis of the post-traumatic stress disorder: A systematic review.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a stressor-related disorder that affects a significant proportion of the population worldwide. De...

Multimodal AI for early prediction of adverse clinical outcomes in acute pancreatitis.

BACKGROUND: Conventional clinical scoring systems and contrast-enhanced computed tomography (CECT) interpretation provide limited accuracy in predicti...

Symbolic Acceleration and Embodied Integration: Toward a Developmental Framework of Identity Reconstruction.

Identity is a multi-level integrative process involving coordinated development across affective, symbolic, and embodied systems-a process of progress...

Radiologist Perceptions of an AI Tool for Intracranial Hemorrhage Detection in Teleradiology: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) detection tools for intracranial hemorrhage (ICH) are increasingly integrated into radiology workflows. In re...

Integrating risk prioritization and interpretable machine learning to inform PFAS management in an urban aquatic system.

Per- and polyfluoroalkyl substances (PFASs) pose persistent challenges to urban environmental management due to their complex sources, ongoing substit...

Novel Online Platform for Trauma Care-Integrating Trauma Phenotypes to Optimize the Trauma and Injury Severity Score Model: Retrospective Cohort Study.

BACKGROUND: Severe trauma remains a leading cause of admission to the intensive care unit. The Trauma and Injury Severity Score (TRISS) is an establis...

An explainable machine learning approach to predict fragility fractures and the identification of important features.

In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites, using t...

A large-scale vision foundation model for musculoskeletal radiographs.

Artificial intelligence (AI) has shown promise in detecting and characterizing musculoskeletal diseases from radiographs. However, most existing model...

Uncertainty-aware spatio-temporal contrastive graph neural networks for cyber financial fraud detection and risk management.

Financial fraud detection requires screening massive transaction networks where evolving topologies, extreme label sparsity, and asymmetric misclassif...

Integrating network toxicology, machine learning, and single-cell sequencing to reveal the FASN-mediated role of phenolic endocrine disruptors in water in promoting prostate cancer.

BACKGROUND: Phenolic endocrine-disrupting chemicals (EDCs) like nonylphenol (NP) and octylphenol (OP) are widespread water pollutants. Their estrogen-...

Continuum damage modeling of fatigue failure in whole bone under combined compression-torsional loading: A hybrid approach with machine learning integration.

Repetitive loading of bone is associated with microdamage accumulation and material property degradation that may ultimately result in fatigue fractur...

Integrating MIKE model simulations with CNNs for rapid and accurate urban flood prediction.

Rapid prediction of urban pluvial flooding is an important tool for mitigating current urban flooding disasters. This paper constructs a fast predicti...

Performance comparison of a neuro-symbolic large language model system versus conventional AI models and human experts in cholangitis management.

BACKGROUND: Large language models (LLMs) have shown promising results in medical decision support; Background: Large language models (LLMs) have demon...

Development and validation of a machine learning model predicting post-tonsillectomy hemorrhage.

PURPOSE: To develop and validate machine learning models to predict post-tonsillectomy hemorrhage. METHODS: This was a machine learning analysis of a ...

Expert Validation of an Artificial Intelligence-Enabled Trial Matching Solution Using Real-World Data From Patients With Cancer.

PURPOSE: To validate the performance of an AI system (TRIAGE) for cancer trial eligibility screening using real-world longitudinal electronic health r...

Environmental Levels of Sodium p-Perfluorous Nonenoxybenzene Sulfonate Induce Nephritis in Renal Proximal Tubular Epithelial Cells via Modulation of Estrogen Signaling Pathways.

Sodium p-perfluorous nonenoxybenzene sulfonate (OBS), widely used as an alternative to per- and polyfluoroalkyl substances, has been implicated in tox...