Domestic Violence

Prospective Data Curation Enables High-Performance Artificial Intelligence for Diabetic Retinopathy Screening in a Resource-Limited Setting.

PURPOSE: To determine whether a high-quality, prospectively curated dataset can, by itself, enable the development of robust and clinically effective artificial intelligence as a medical device (AIaMD) models for diabetic retinopathy (DR) screening, even with minimal artificial intelligence (AI) infrastructure. This study evaluates whether careful data curation, standardized acquisition, and rigor...

Commercial AI Model Diagnostic Accuracy for Intracranial Large- and Medium-Vessel Occlusion in Emergency CT Angiography.

The diagnostic accuracy of AIDOC-VO, the first commercial artificial intelligence tool for intracranial large-and medium-vessel occlusion (LVO/MeVO) detection on head-and-neck CT angiography (CTA), was evaluated in a multicenter emergency setting. A prospective diagnostic-accuracy study of 3,031 adult CT angiograms (mean age, 67.3 years ± 16.4 [SD]; 1,549 females) acquired March-July 2024 across a...

MAISNet: A Multi-Species Integrated Graph Neural Network for Acetylcholinesterase Inhibitor Screening.

MOTIVATION: Global population aging has led to a rapid increase in neurodegenerative disorders such as alzheimer's disease (AD). Although existing dru...

Deep learning in population-based screening for glaucoma.

BACKGROUND/AIMS: Deep learning algorithms have shown promise for glaucoma detection using retinal imaging. The Northern Finland Birth Cohort Eye Study...

AI triage of duodenal biopsies improves workflow.

AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopatholog...

Prompt engineering of large language models for paper screening in medical meta-analyses and systematic reviews: A prospective comparative study.

Interest in large language models (LLMs) as a tool for meta-analyses and systematic reviews (MA/SRs) is growing. We prospectively developed 515 unique...

Building a tactical medical chatbot for conflict and low-resource settings: A low-code platform approach.

BACKGROUND: Conflict zones severely disrupt healthcare access, with millions affected by armed conflicts. The lack of standardized medical guidance ex...

Risk-Guided Atrial Fibrillation Screening With Artificial Intelligence-Enabled Electrocardiogram Models: A VITAL-AF Trial Analysis.

BACKGROUND: Screening for atrial fibrillation (AF) may lead to earlier detection and initiation of preventive measures. Current AF screening approache...

Minimum joint space width demonstrates higher inter-and intra-observer reliability than Kellgren-Lawrence grading in knee osteoarthritis.

PURPOSE: The purpose of this systematic review was to compare the inter- and intra-observer reliability of Kellgren-Lawrence (KL) grading versus minim...

Measuring Technology-Facilitated Sexual Violence and Abuse: Scoping Review of Existing Measures.

BACKGROUND: Technology-facilitated sexual violence and abuse (TFSVA) encompasses sexual harms perpetrated through digital means. Rapid developments in...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...

Cardiovascular toxicity of ethyl maltol exposure: a comprehensive investigation from virtual screening to experimental validation.

Ethyl maltol is a ubiquitous synthetic flavor enhancer. Despite its widespread use in foods, beverages, and electronic cigarettes, and its potential f...

Using Large Language Models to Determine Reasons for Missed Colon Cancer Screening Follow-Up.

BACKGROUND: Identifying reasons for missed preventive care, such as follow-up colonoscopy after an abnormal stool-based colon cancer screening test, i...

AI-based classification of pediatric sagittal skeletal patterns using multi-view facial photographs.

OBJECTIVE: The increasing global demand to assess pediatric skeletal malocclusions poses a growing challenge, as current screening methods are depende...

Evaluating the heterogeneous treatment effects of major depression polygenic risk scores on self-harm using causal forest.

BACKGROUND: Self-harm, defined as non-fatal self-inflicted harm regardless of suicidal intent, is a critical global health issue influenced by the int...

An interpretable machine learning tool for rheumatoid arthritis screening: integrating novel cellular morphological parameters with routine blood count indices.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease that can cause significant disability. Early detection is vital for improving ou...

Cost-effectiveness of AI-enhanced breast cancer screening in Iran: a microsimulation study.

BACKGROUND: Recognized worldwide as a major health threat and Sustainable Development Goal priority, breast cancer places an especially heavy clinical...

Using Machine Learning to Improve Screening for Oropharyngeal Dysphagia in Hospitalized Versus Primary Care Adult Patients With COVID-19 Disease: Retrospective Observational Study.

BACKGROUND: Oropharyngeal dysphagia (OD) commonly occurs in patients with COVID-19 disease, posing diagnostic challenges due to isolation protocols. O...

Development and Validation of a Web Calculator for Predicting the Risk of Lower Limb Varicose Veins.

The aims of the present study were to develop and validate a predictive model for lower limb Varicose Veins, and to visualize the results using a web ...

Diagnostic accuracy and deployment readiness of AI for burn depth assessment across imaging modalities: a PRISMA-DTA systematic review and meta-analysis.

BACKGROUND: AI-based burn depth assessment is rapidly emerging, yet evidence for diagnostic accuracy, generalizability, and deployment readiness remai...