Domestic Violence

Machine learning models for reducing false positives in Fluorometric newborn screening of phenylketonuria: Development, validation, and clinical application.

BACKGROUND: Fluorometric newborn screening for phenylketonuria (PKU) is widely used but plagued by high false positives (FPs), leading to unnecessary follow-ups and parental anxiety. Machine learning (ML) models may optimize screening efficiency by reducing FPs while preserving sensitivity. METHODS: A retrospective study used fluorometric PKU screening data from 493,652 neonates (2022-2024) at She...

[Artificial intelligence in diabetic retinopathy screening].

INTRODUCTION: Visual impairment and blindness continue to represent a substantial disease burden in Hungary. According to national epidemiological data, the combined prevalence of bilateral blindness and severe visual impairment among individuals aged 50 years and older is approximately 0.9%, and international estimates suggest that around 90% of vision loss cases could be prevented or treated wit...

Undergraduate medical students and artificial intelligence: A global systematic review and meta-analysis using a knowledge-attitude-practice framework.

BACKGROUND: Artificial intelligence (AI), including deep learning and large language models, is increasingly reshaping healthcare and medical educatio...

Identification of zinc finger protein-related feature genes in ischemic stroke via explainable machine learning: A comprehensive analysis.

BACKGROUND: Zinc finger proteins (ZFPs) play important roles following ischemic stroke (IS), but systematic investigations into their potential as bio...

Development of Machine Learning-Driven Dual-Task Gait Test Model for Cognitive Impairment Screening.

OBJECTIVE: To develop an artificial intelligence (AI)-aided dual-task gait test model for scalable, high-throughput cognitive impairment screening. DE...

Evaluating Elicit's systematic reviews workflow in an umbrella review on air pollution and acute lower respiratory infections: a methodological study for quality appraisal.

BACKGROUND: The exponential growth of scientific publications has increased the complexity of evidence synthesis. Systematic reviews remain essential ...

Shift-Specific Patterns of Nursing Workloads in the Emergency Department: AI Powered Analysis.

AIM: To identify and differentiate workload patterns across shifts and to provide evidence for optimizing nursing workforce allocation in emergency de...

Artificial Intelligence Chatbots' Performance on Dental Trauma Case-based Queries: Examining the Effect of Prompt and Content Engineering.

INTRODUCTION: Traumatic dental injuries (TDIs) require prompt and accurate guidance, yet little is known about how the prompting influences the qualit...

Multi-task deep learning for sub-clinical screening of mood and sleep disturbances using physical activity biomarkers.

BACKGROUND: Sub-clinical screening for mood disorders and sleep disturbances remains challenging due to limited accessibility of mental health screeni...

External Validation of a mHealth Tool for Detecting Gingival Inflammation in Community-Dwelling Older Adults.

OBJECTIVE: This study aimed to externally validate the screening performance of a pro-social (equitable, accessible), explainable AI (XAI)-guided mobi...

Fluid-based biomarkers of amyotrophic lateral sclerosis: recent advances and future prospects.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder with no definitive cure. The absence of specific diagnostic biomarkers...

A Reproducible Hierarchical Virtual Screening Framework Integrating Scaffold-Aware Machine Learning, Ensemble Docking, and Molecular Dynamics: Application to IDO1.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a heme-containing enzyme implicated in cancer immune escape and remains an attractive therapeutic target despi...

An integrated computational-experimental approach identifies Malate Synthase G as therapeutic target to disrupt carbon metabolism in chronic Pseudomonas aeruginosa infection.

Pseudomonas aeruginosa is a leading cause of nosocomial infections, particularly in individuals with a compromised immune system. Due to its strong ad...

Compliance with the CONSORT AI Extension in Orthopaedic Randomized Controlled Trials.

BACKGROUND: The utilization of artificial intelligence (AI), such as machine learning, in health care has risen exponentially, underscoring the necess...

Impacts of human and digital scribes on improving physician wellness and reducing administrative burden: a scoping review protocol.

INTRODUCTION: The rise in administrative burden on physicians is becoming increasingly recognised as a significant contributor to burnout and job diss...

Machine learning models for early mortality prediction in trauma patients using public data: a nationwide retrospective study.

BACKGROUND: Trauma is a leading cause of morbidity and mortality worldwide, particularly in younger populations. Early identification of high-risk tra...

The art of semantics in radiology reporting.

Radiology reports are the primary product of diagnostic radiology, yet the language in which they are written is rarely taught formally. The differenc...

Integrated multi-endpoint hazard prioritization of unregulated industrial contaminants: A safety-first screening framework for emerging environmental threats.

The rapid expansion of the industrial chemical space has outpaced regulatory oversight, creating a critical regulatory and environmental blind spot re...

Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.

Anxiety disorders are common and impairing mental health conditions. Using data from 26,378 adults in the German National Cohort Study (NAKO), we inve...

Development and Validation of an Image-Based Deep Learning Tool for Identification of Xylazine-Associated Wounds.

OBJECTIVES: Accurate identification of xylazine-associated wounds (XAWs) is critical to providing timely and optimal management; however, discerning t...