Domestic Violence

Prevalence and Predictors of Silent Vertebral Compression Fractures: A Cross-Sectional Population-Based Study Using UK Biobank Imaging Data

To estimate the prevalence of silent vertebral compression fractures (VCF) in an asymptomatic population and to assess the demographic and clinical predictors using data from the UK Biobank. A cross-sectional study using artificial intelligence-assisted six-point morphometry of dual-energy x-ray absorptiometry spine images. UK Biobank imaging study at Stockport clinical research facility. 2 446 as...

Prognosis After First-Trimester Threatened Miscarriage: A Systematic Review, Prognostic Accuracy Meta-Analysis, And Prediction Modelling Review

Threatened miscarriage represents one of the most prevalent obstetric emergencies globally. Nevertheless, women experiencing first-trimester bleeding with a viable intrauterine pregnancy are predominantly advised based on empirical experience rather than on precisely quantified risks. Over the past forty years, numerous biochemical, ultrasound, and clinical predictors have been proposed. More rece...

Predicting Alzheimer’s Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning Models

There is need to detect and intervene in pre-clinical phases of Alzheimer’s disease (AD). Electronic health records (EHRs) may help predict AD using m...

Measuring the Quality of AI-Generated Clinical Notes: A Systematic Review and Experimental Benchmark of Evaluation Methods

High-quality clinical documentation is essential for safe, effective care, yet producing it is time consuming and error prone. Large language models (...

Machine learning-driven prediction of opioid and stimulant-related drug overdose fatalities: Analysis of the potential fourth wave

Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of all overdose deaths in the U.S. The Centers for Dise...

Acoustic Analysis of Primary Care Patient-provider Conversations to Screen for Cognitive Impairment

Cognitive impairment (CI) is often under detected in primary care due to time and resource constraints. Passive analysis of clinical dialogue may offe...

An integrated analytical framework for gender-based violence research: A simulation study combining machine learning and causal inference

Current research on Gender-Based Violence (GBV) typically separates predictive machine learning and causal inference into distinct analytical silos. Y...

Assessing Statistical Practices of Existing Artificial Intelligence (AI) Models for Lung Cancer Detection, Prognosis, and Risk Prediction: A Cross-Sectional Meta-Research Study Supplemented by Human and Large Language Model (LLM)-Directed Quality Appraisal

Artificial intelligence (AI) models with medical images as input data are increasingly proposed to support clinical decisions in lung cancer screening...

Machine learning-optimized perinatal depression screening: Maximum impact, minimal burden

Perinatal depression affects up to 30% of pregnant and postpartum women, which has increased since the COVID-19 pandemic, making rapidly identifying a...

Opportunistically Detecting Signs of Hypertension on a Consumer Smartwatch

Hypertension is a silent killer, with over half of affected adults unaware of their condition1,2. This lack of awareness is a major concern, as early ...

Demographics, Overlap, and Latency of Severe Cutaneous Adverse Reactions in an FDA Database

Severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS-TEN), drug reaction with eosinophilia a...

Evaluation of SSI risk prediction model after spinal surgery: A systematic review and critical appraisal

This study aimed to systematically review and critically evaluate the risk of bias and applicability of surgical site infection (SSI) risk prediction ...

European strategies in the screening of biliary atresia: a scoping review.

BACKGROUND: Biliary atresia (BA) is a rare condition that meets the criteria for neonatal screening. Taiwan province of China led the way in BA screen...

Intimate partner violence and stress-related disorders: from epigenomics to resilience.

Intimate Partner Violence (IPV) is a major public health problem to be addressed with innovative and interconnecting strategies for ensuring the psych...

Providing a Prostate Cancer Detection and Prevention Method With Developed Deep Learning Approach.

Prostate cancer is the second most common cancer among men worldwide. This cancer has become extremely noticeable due to the increase of prostate can...

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans.

Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2...

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and M...

Is Generative AI Increasing the Risk for Technology-Mediated Trauma Among Vulnerable Populations?

The proliferation of Generative Artificial Intelligence (Generative AI) has led to an increased reliance on AI-generated content for designing and dep...

[Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms].

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting ...

Automatic large-scale political bias detection of news outlets.

Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when intera...