Domestic Violence

Commercial AI for CT lung cancer screening: product capabilities, coverage of nodule management tasks and supporting evidence.

OBJECTIVES: To characterize the capabilities of CE-marked AI products for lung nodule analysis in lung cancer screening (LCS), quantify their coverage of tasks defined in nodule management recommendations, and assess their peer-reviewed evidence. MATERIALS AND METHODS: Six core tasks in LCS (nodule detection, classification, measurement, growth assessment, malignancy risk estimation, and structure...

Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.

BACKGROUND: In critically injured trauma patients, tools that stratify injury severity and estimate mortality are essential. Fuzzy logic (FL) enables the creation of accurate, interpretable models but requires decision rules, which can be generated using machine learning (ML) techniques like classification trees (CT). Our objective was to develop a hybrid model combining fuzzy logic and classifica...

Smartphone-based lightweight AI system for real-time multiple anterior segment disease screening: development and real-world validation.

BACKGROUND: Anterior segment diseases are a major global cause of preventable blindness, especially in regions with limited access to specialized opht...

Divergent neuropsychiatric and systemic toxicity profiles of abemaciclib and palbociclib: a triangulation study integrating pharmacovigilance, genetic epidemiology, and multi-omics profiling.

Cyclin-dependent kinase 4/6 inhibitors improve outcomes in hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breas...

Examining the utility of digital phenotyping for the prediction of intrusive experiences.

Background: Intrusive experiences related to witnessing a traumatic event are the core symptom of post-traumatic stress disorder (PTSD), and have been...

Ensemble Machine Learning for Interpretable Prediction of Acute Toxicity in Metal-Organic Framework Linkers.

Metal-organic frameworks (MOFs) are promising platforms for drug delivery due to their high porosity, tunable chemistry, and controlled release capabi...

Risk Stratification for Breast Cancer Screening: AJR Expert Panel Narrative Review.

Early detection of breast cancer reduces mortality and is influenced by screening strategies. The balance of benefits and harms within any screening p...

Detecting Patterns of Intimate Partner Violence Using Qualitative Analyses and Machine Learning Algorithms.

Intimate partner violence (IPV) survivors increasingly use social media platforms to share their experiences and to seek help and support for their IP...

Geometric Morphometric-Based Estimation as an Aid for Naso-Orbito-Ethmoidal Trauma Management.

The naso-orbito-ethmoid (NOE) region comprises complex anatomy, and as such, NOE fractures present with a challenge during reconstruction. Restoring t...

Automated full-text screening and accelerated reviews using large language models with context-aware agents: an exploratory analysis in biomarker research.

AIMS: Artificial intelligence (AI) tools utilizing large language models (LLMs) can accelerate scientific literature reviews by automating title, abst...

Artificial Intelligence Models Using Magnetic Resonance Imaging to Predict Response to Chemoradiotherapy in Rectal Cancer: A Systematic Review.

BACKGROUND: Pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC) is a key prog...

EDC Profiler: A High-Throughput Screening Server for Identifying Endocrine Disrupting Chemicals toward Multiple Nuclear Receptors.

Endocrine disrupting chemicals (EDCs) are associated with various adverse health outcomes, thus necessitating high-throughput screening. However, curr...

Artificial Intelligence in the Trauma Bay: A Pilot Comparison With Surgical Trainees.

BackgroundLarge language models (LLMs) have demonstrated strong performance on general medical knowledge assessments; however, their accuracy within h...

Cybersecurity in Healthcare: A Systematic Review and Narrative Analysis.

BACKGROUND: Cybersecurity attacks in healthcare have increased in number and severity over the last decade. Healthcare targets are ten times more valu...

Risks and Harms of Conversational Artificial Intelligence (CAI) Chatbot Use Among US Youth.

INTRODUCTION: Conversational AI (CAI) chatbots are widely used by adolescents for instruction, entertainment, companionship, and advice, but concerns ...

The Rise in Artificial Intelligence and Machine Learning Models to Screen for Cleft-Related Velopharyngeal Dysfunction: A Systematic Review.

ObjectiveTo systematically review literature on the use of artificial intelligence (AI) and machine learning (ML) models for detecting velopharyngeal ...

Breaking the Black Box: Interpretable AI Achieves Superior Hemorrhage Detection with the Compensatory Reserve Measurement.

Hemorrhage remains the leading cause of preventable trauma death, with traditional vital signs failing to detect blood loss until 25-30% volume deplet...

Cost-effectiveness of latent tuberculosis infection screening using interferon-gamma release assays among migrants to Japan: a Markov modelling study incorporating social vulnerability and access barriers.

OBJECTIVE: This study aims to evaluate the cost-effectiveness of latent tuberculosis infection (LTBI) screening strategies using interferon-gamma rele...

Development and validation of a machine learning-based screening tool for early detection of adolescent suicide risk.

BACKGROUND: Adolescent suicide remains a significant public health concern, yet existing suicide screening instruments primarily focus on already mani...

Auto Machine Learning for Diabetic Retinopathy Screening: A Head-to-Head Multiplatform Comparison Against Human Graders and IDx-DR.

PURPOSE: To benchmark multiple automated machine learning (AutoML) platforms for diabetic retinopathy (DR) screening from fundus photographs using a u...