Identifying and Reporting Dependent Adult abuse

Generative AI in EFL contexts: Q-methodological analysis of cognitive dissonance patterns and self-regulation strategies among Chinese tertiary learners.

Generative Artificial Intelligence (GenAI) has recently attracted growing attention in English as a Foreign Language (EFL) education, offering opportunities for personalised learning and efficiency gains. Yet, alongside these benefits, learners also face psychological tensions, particularly cognitive dissonance, that remain underexplored in current research. Prior work has often examined GenAI use...

Can AI write reports like a radiologist? A blinded evaluation of large language model-generated lumbar spine MRI reports.

BACKGROUND: To compare the quality and clinical usefulness of large language model (LLM)-generated lumbar spine magnetic resonance imaging (MRI) reports with radiologist-written ones and assess whether medical professionals can distinguish between them. MATERIALS AND METHODS: This retrospective observational single-center study was approved by the local ethics committee. A total of 125 lumbar spin...

Evaluation of GPT-5 for Esophageal Cancer Staging Using Fluorodeoxyglucose Positron Emission Tomography Maximum-Intensity Projection Images: Comparative Pilot Study.

BACKGROUND: Accurate esophageal cancer staging relies on 18F fluorodeoxyglucose positron emission tomography (18F FDG-PET), but its interpretation is ...

Het2Gene: a phenotype-driven model for gene prioritization by heterogeneous graph embedding.

Mendelian genetic diseases pose a significant global health burden. Early identification of causative genes is crucial for halting disease progression...

Prospective pilot evaluation of a deep learning model for kidney stone detection on CT using a web-based workflow platform.

Rapid and reliable detection of kidney stones on non-contrast abdominal CT is essential for timely decision-making in emergency radiology. However, ri...

Standardizing case definitions for hoof lesions and lameness: A scoping review to improve machine learning applications in dairy cattle.

Lameness in dairy cattle, primarily caused by hoof lesions, remains a widespread issue in North America with significant welfare, economic, and sustai...

Artificial intelligence-enhanced microsurgical training: a systematic review.

Artificial intelligence (AI) offers objective, adaptive tools for skill enhancement in microsurgical training, but evidence is fragmented. This system...

Assessing the Reliability of Large Language Models for Evaluation of Risk of Bias in Randomized Clinical Trials.

OBJECTIVE: Systematic reviews depend on rigorous risk-of-bias (RoB) assessments to ensure credibility, yet manual evaluation using the Cochrane RoB 2 ...

Unsupervised domain adaptation for medical image segmentation using adaptogen-perturbation.

Domains shift originated from differences in devices or patients in the medical field, poses a significant challenge when applying pre-trained models ...

Predicting Surgical Outcomes in Breast Reconstruction With Machine Learning: A Systematic Review.

INTRODUCTION: The applications of artificial intelligence (AI) in plastic surgery have grown considerably in recent years. As large patient datasets b...

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.

BACKGROUND: Stroke is a complex, multidimensional disorder influenced by interacting inflammatory, immune, coagulation, endothelial, and metabolic pat...

Automated Report Generation in Ophthalmology: Integrating Artificial Intelligence, Multimodal Imaging, and Clinical Data.

Artificial intelligence (AI) has emerged as a transformative force in ophthalmology, enabling automated, accurate, and efficient clinical reporting. T...

Machine learning estimates for G20 subnational urban GHG emissions from 2000-2020.

Reliable, comparable greenhouse gas (GHG) emissions data at the subnational level remain scarce, despite growing expectations for cities and regions t...

Healthcare practitioner involvement in data-driven clinical decision support development and evaluation: Critical narrative review of recommendations.

OBJECTIVE: While healthcare practitioner (HCP) involvement is widely acknowledged as essential for the development and evaluation of trustworthy data-...

PGST: A prototype-guided parameter-efficient network for spatial transcriptomics prediction.

Spatial transcriptomics (ST) aims to decode spatially resolved gene expression patterns while preserving tissue morphology. Current methods tend to us...

Application of AI Models for Preventing Surgical Complications: Scoping Review of Clinical Readiness and Barriers to Implementation.

BACKGROUND: The impact of surgical complications is substantial and multifaceted, affecting patients and their families, surgeons, and health care sys...

Artificial intelligence to support ultrasound in the detection of developmental dysplasia of the hip : a scoping review.

AIMS: Ultrasound is a highly sensitive method to detect developmental dysplasia of the hip (DDH). However, the cost of expert sonographers performing ...

Artificial intelligence for surgical care in war-torn sudan: Feasibility, barriers, and ethical perspectives from a conflict zone.

BACKGROUND: Artificial intelligence (AI) offers transformative potential for clinical care, yet its deployment in conflict-affected, low-resource sett...

CLAIRE: a unified framework for reporting and assessing artificial intelligence in diagnostic imaging.

Artificial intelligence (AI) models for diagnostic imaging face reproducibility challenges due to inconsistent reporting. Existing guidelines also lac...

Comparing decentralized machine learning and AI clinical models to local and centralized alternatives: a systematic review.

This systematic review evaluates how decentralized learning (DL) approaches-e.g., federated learning, swarm learning, ensemble-compare with traditiona...