Domestic Violence

Risk-aware explainable multi-output workflow for early-stage screening of building heating and cooling load indicators.

Early-stage design decisions largely determine a building's operational energy demand, but benchmark-trained surrogate models must be used with explicit validity limits. This paper presents a risk-aware, reproducible and explainable multi-output machine-learning workflow for screening simulated heating load (HL) and cooling load (CL) indicators from concept-stage geometric and envelope parameters....

Clinical Risk Management and Patient-safety Research: A Large-scale Bibliometric Mapping of the Field and Its Emerging Directions (Master vs. 2021-2025).

BACKGROUND: To map the evolution, knowledge structure, and emerging directions of clinical risk management (CRM) and patient-safety research by contrasting a full-timespan corpus with the most recent 5-year subset. METHODS: Records were retrieved from Web of Science Core Collection (n=23,498; 1986-2026) and Scopus (n=51,710; 1958-2026) using harmonized queries targeting patient safety, adverse eve...

A single-camera video-based assessment of locomotive syndrome using pose-silhouette fusion model.

Locomotive syndrome (LS), characterized by declining mobility due to musculoskeletal disorders, significantly affects older adults and is highly preva...

Correction to: Prediction of severe erectile dysfunction after penile fracture repair: machine learning analysis results from the reconstruction and trauma working group of the society of urological surgery (RAT-SUS).

[This corrects the article DOI: 10.1093/sexmed/qfaf101.].

LLM-Assembled Multiscale Cascades for High-Throughput Screening: The Case of Thermoelectric Materials.

High-throughput screening workflows often rank materials with a sequence of filters, but a single sequence can hide how strongly the final ranking dep...

Adherence of CLAIM in Artificial Intelligence Research: A Cross-Sectional Study.

OBJECTIVE: To analyze the adherence of Checklist for Artificial Intelligence (AI) in Medical Imaging (CLAIM) in top medical imaging journals. METHODS:...

Deep Learning Models for Detection of Periapical Radiolucent Lesions on Panoramic Radiographs: A Systematic Review and Meta-Analysis.

BACKGROUND: Panoramic radiographs are used routinely to screen dental conditions and treatment patterns. Recently, numerous studies have suggested tha...

CT in adult patients with Polytrauma: current practices, protocol optimization, structured reporting and future directions.

Computed tomography [CT] is the frontline imaging modality for the assessment of polytrauma patients because of its speed, diagnostic accuracy and inf...

Value operating system: a practical framework to measure outcomes-per-cost at the episode level.

OBJECTIVE: To specify a value operating system (VOS) and its executable metric-the Value Index (VI)-that expresses risk-adjusted outcomes-per-episode-...

Towards trustworthy AI-driven cuffless blood pressure monitoring.

Cuffless blood pressure monitoring is becoming increasingly feasible with the rise of wearable technologies, offering significant promise for preventi...

AI and machine learning for early identification of eating disorders: a narrative review and Indian contextual insights.

BACKGROUND: Eating disorders (EDs) are a growing global health concern and are increasingly associated with negative body-image perceptions linked to ...

Machine learning-powered audio-omics processing method as an auxiliary diagnostic approach for advanced nasopharyngeal carcinoma.

PURPOSE: Nasopharyngeal carcinoma (NPC) is located in the nasopharyngeal mucosa and is a malignant tumour of the head and neck, and approximately 70% ...

Pediatric radiology informatics within a larger academic practice.

As academic health systems increasingly consolidate with unified electronic health records (EHR), picture archiving and communication systems (PACS), ...

Exploring Non-Embodied AI-Based Digital Companions for Older Adults in Aging and Care Contexts: Protocol for a Scoping Review.

BACKGROUND: Conversational artificial intelligence (AI) technologies are increasingly positioned as a response to social isolation, loneliness, and un...

Vision-Based Artificial Intelligence Technologies for Epilepsy Monitoring: Scoping Review and Taxonomy Development Study.

BACKGROUND: Artificial intelligence (AI) technologies for vision-based epilepsy monitoring are advancing rapidly in health care. Despite growing resea...

Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.

Structure-based virtual screening (VS) via molecular docking is a pivotal approach for hit identification. Many artificial intelligence (AI)-powered p...

Advanced machine learning-based screening for primary aldosteronism with plasma steroids, potassium, and renin.

Commonly used screening tests for primary aldosteronism (PA) provide suboptimal diagnostic accuracy, particularly with antihypertensive medication use...

Supporting Literature Reviews: A Comparison Between Human and Generative Artificial Intelligence Screening for a Scoping Review.

Scoping reviews are used to map the literature within a field or discipline, summarize existing evidence, and identify gaps in knowledge. Conducting a...

Consensus on the use of artificial intelligence in the management and measurement of vestibular schwannomas: A protocol for a modified delphi consensus.

INTRODUCTION: The assessment of vestibular schwannomas (VS) requires a standardized approach as growth is a key element in defining treatment strategy...

NeuroCypher ASD: Machine Learning with Knowledge Graph-Based Representation for ASD Screening in Toddlers.

Autism Spectrum Disorder (ASD) screening often relies on structured questionnaires. Yet these data are not always easy to interpret or use in practice...