Domestic Violence

Carbonyl-Modulated Lowest Unoccupied Molecular Orbital Energy Directs Machine Learning-Assisted Screening of Electrolyte Additives Toward Ultra-Stable Zinc Metal Anodes.

The commercialization of aqueous zinc-ion batteries has long been hindered by side reactions stemming from zinc anode interfacial instability. Organic molecular additives offer an effective solution. Here, using lowest unoccupied molecular orbital (LUMO) energy and solubility as dual screening criteria, a novel high-precision Organic Molecular Attention Prediction Graph Neural Network is developed...

Artificial Intelligence-Assisted Wireless Handheld Ultrasound for Screening Developmental Dysplasia of the Hip in Infants.

OBJECTIVES: Ultrasonography is increasingly the preferred method for infant hip screening to enable timely diagnosis and treatment of developmental dysplasia of the hip (DDH). However, its reliance on experienced specialists and bulky equipment limits its application in routine screening, particularly in resource-limited and remote settings. We aimed to develop an artificial intelligence wireless ...

Standardizing PSMA PET/CT reporting in prostate cancer: from structured frameworks to AI-assisted interpretation.

PSMA PET/CT is increasingly used for prostate cancer staging, restaging, treatment selection, and therapy response assessment. In parallel, several in...

Miniaturization in robotic surgery: a bibliometric and science mapping analysis of technological evolution and clinical translation (1996-2026).

Miniaturization has emerged as a major technological trajectory in robotic surgery, encompassing single-port systems, flexible endoscopic platforms, c...

The Role of Artificial Intelligence in the Prevention of Intimate Partner Violence and Sexual Violence: A Scoping Review of the Literature.

Intimate partner and sexual violence (IPV/SV) remain pervasive global public health issues. Prevention efforts typically occur at the primary level (p...

Prognostic value of AI-derived epicardial adipose tissue beyond coronary artery calcium on chest CT in an asymptomatic screening population.

BACKGROUND: The incremental prognostic value of epicardial adipose tissue (EAT) quantified on nongated, noncontrast chest CT beyond conventional risk ...

Machine learning for scalable obstructive sleep apnea risk screening using digital phenotyping from wearable devices and clinical scales.

Obstructive sleep apnea (OSA) is common yet frequently underdiagnosed, partly because overnight polysomnography (PSG) is logistically burdensome and a...

Regulating digital surgery to balance safety and innovation: a SAGES white paper.

BACKGROUND: Digital surgery technologies, including robotic systems, artificial intelligence (AI) algorithms, augmented reality platforms, and advance...

Comparative predictive accuracy of machine learning versus traditional statistical methods for diabetes-related complications: A systematic review and analysis.

AIMS: To compare the predictive accuracy of machine learning models versus traditional statistical models for predicting and detecting long-term compl...

Simultaneous learning of static and dynamic charges.

Long-range interactions and electric response are essential for accurate modeling of condensed-phase systems, but capturing them efficiently remains a...

Assessing the reproducibility of a bioimage analysis workflow characterising tissue flow in Drosophila.

Reproducibility challenges in bioimage analysis are common. The proliferation of tools and workflows creates a complex ecosystem that is difficult to ...

Prognostic prediction models for psoriatic arthritis in psoriasis: A systematic review.

BACKGROUND: Psoriatic arthritis is a chronic inflammatory arthropathy that affects up to 22% of individuals with psoriasis. Identifying patients at hi...

Improving End-of-Life Screening in the Emergency Department With Collaborative Artificial Intelligence.

STUDY OBJECTIVES: To compare end-of-life predictions as measured by the physician-answered surprise question (SQ), "Would you be surprised if this pat...

AI-Driven Decision Thresholds in Cariology: A Systematic Review of Lesion Stage Detection on Bitewing Radiographs.

INTRODUCTION: This systematic review evaluates the stage-specific diagnostic accuracy of artificial intelligence (AI) models for caries detection and ...

Evaluation of Five Large Language Models for Parental Education in Pediatric Anesthesia: Reliability and Readability Study.

BACKGROUND: Although large language models (LLMs) show potential for patient education, their accuracy, usability, and comprehensibility lack validati...

End-to-End PET/CT Interpretation and Quantification with an LLM-Orchestrated AI Agent: A Real-World Pilot Study.

Although deep learning models have improved individual PET analysis, image processing, and quantification tasks, end-to-end automation from raw DICOM ...

Large Language Models Provide Accurate but Potentially Unsafe Answers to Multimodal Critical Care Medicine Board Review Questions.

OBJECTIVES: To evaluate the performance of Chat Generative Pre-Trained Transformer-4 Omni (ChatGPT-4o) in answering multimodal critical care board rev...

Large language models for systematic reviews were reported to perform well but rarely with verifiable safeguards: a cross-sectional study.

OBJECTIVES: The application of large language models (LLMs) to systematic review tasks is rapidly expanding, yet the transparency and methodological r...

Applying machine learning to pharmacovigilance data: A proof-of-concept study.

AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance d...

REFLECTIVE-TIAB: cost-effective prompt optimisation for large language model-based title and abstract screening in literature reviews.

BACKGROUND: Title and abstract screening is a labor-intensive stage of systematic reviews. Large language models (LLMs) can automate this process, but...