Domestic Violence

Biomedical Large Language Models and Prompt Engineering for Causality Assessment of Individual Case Safety Reports in Pharmacovigilance.

BACKGROUND: Biomedical Large Language Models (LLMs) combined with prompt engineering offer domain-specific reasoning, yet their application to individual-level causality assessment remains unexplored. This study evaluated five combinations of biomedical LLMs, prompting strategies, and causality algorithms by comparing their agreement with two human expert evaluators. RESEARCH DESIGN AND METHODS: A...

The Evolution of Precision Anti-Doping From UGT2B17 Polymorphism Insights to Integrated Detection Frameworks.

Screening for endogenous anabolic-androgenic steroid abuse has long relied on the urinary testosterone/epitestosterone (T/E) ratio. However, this metric is significantly influenced by genetic polymorphisms such as copy number variations in the UGT2B17 gene. Because the distribution of this genetic heterogeneity varies across ethnic populations, individuals with the del/del genotype face a higher r...

Evaluation of suicide behavior screening tools using machine learning and variable importance measures.

Suicide screening in military primary care settings is often conducted with a small number of self-report questions. The PRImary care Screening Method...

Convolutional Neural Networks in Radiology: Principles, Clinical Applications, and a Practical Framework for Radiologists.

Artificial intelligence is increasingly embedded within radiology workflows. In radiology, large language models may support reporting and communicati...

Automated orbital wall fracture detection and severity classification of ocular injuries using deep learning.

Orbital fractures are frequently encountered in maxillofacial trauma and can be associated with severe globe injuries (SGI). Accurate and timely diagn...

An evaluation of artificial intelligence assisted prostate biopsy reporting in the Articulate Pro study.

Prospective evidence on clinical utility of AI in histopathology is limited. We conducted a prospective study across three National Health Service spe...

Lung Cancer Screening and Prevention: Beyond Conventional Strategies in a Rapidly Changing Global Milieu.

Lung cancer remains the leading cause of cancer-related mortality worldwide despite advances in early detection and treatment. Furthermore, its epidem...

The CT colonography radiology and data system: history, updates, and future directions.

Computed tomography colonography, also known as virtual colonoscopy, is a minimally invasive imaging technique developed in the early 1990s to evaluat...

AJNR Study-Specific Guidelines for AI in Medical Imaging: Bridging Gaps in Reference Standard and Clinical Evaluation.

The rapid proliferation of artificial intelligence (AI) applications in neuroradiology can lead to heterogeneous study design and reporting that imped...

Innovations in pediatric imaging: a scoping review of the past decade with case illustrations.

BACKGROUND: Imaging plays a fundamental and increasing role in the diagnostic work-up of pediatric patients. Non-invasive imaging methods include ultr...

A collaborative approach to applying Natural Language Processing (NLP) to Domestic Homicide Reviews (DHRs): A study protocol.

Since 2011, there has been a statutory requirement in England and Wales to conduct a Domestic Homicide Review (DHR) into any domestic abuse-related de...

Enhancing aviation safety: An 80-year data-driven model for classification of aviation incident and accident.

The aviation system is safety-critical by nature, and any occurrence of an incident or accident can lead to the loss of human life and significant ope...

Optimizing breast core needle biopsy biomarker throughput using an AI-based workflow.

AIMS: To evaluate the feasibility, appropriate relevance and impact on turnaround time (TAT) of an AI-supported workflow in which AI, integrated in th...

An integrated AI pipeline for automated cytogenetic analysis of bone marrow karyograms in hematological malignancies: A Pix2Pix enhancement and deep learning detection approach.

BACKGROUND: Conventional cytogenetic analysis remains central to the diagnosis and risk stratification of hematological malignancies but is constraine...

Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review.

This scoping review examines the existing literature on the application of artificial intelligence (AI) in screening for eye diseases, with a focus on...

Using a large language model as a third reviewer to augment dual human full-text screening in orthopaedic systematic reviews.

PURPOSE: Large language models (LLMs) are a form of artificial intelligence (AI) that have emerged as potential tools to augment systematic review wor...

QSAR in the AI Era: Reflections for Advancing Chemical Safety Assessment.

Quantitative Structure-Activity Relationship (QSAR) models are increasingly discussed in the broader context of artificial intelligence (AI). Indeed, ...

Large language models and large multimodal models in radiology: opportunities, challenges, and the path toward sustainable long-term clinical integration.

Large language models (LLMs), built on transformer architecture, have emerged as a fundamental tool in natural language processing and contextual reas...

Development, Feasibility, Acceptability, and Usability of an Artificial Intelligence-Powered Chatbot (Suzy) to Support Patients in Substance Use Disorder Recovery: Multiphase Study.

BACKGROUND: Substance use disorder (SUD) remains a major public health crisis in the United States, with significant challenges in treatment access, r...

Systematic review and meta-analysis of machine learning models predicting massive hemorrhage protocol in trauma.

Timely activation of massive hemorrhage protocols (MHP) is critical to prevent exsanguination and improve survival in trauma patients. Current clinica...