Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
INTRODUCTION: This systematic review evaluates the stage-specific diagnostic accuracy of artificial intelligence (AI) models for caries detection and compares their performance with human examiners. METHODS: Following PRISMA 2020 guidelines, four databases (PubMed/Scopus/Embase/ Web of Science) were searched up to October 2025. Nineteen studies using bitewing radiographs and reporting at least one...
BACKGROUND: Estimation of lumbar spinal loads is important for understanding low back pain, guiding ergonomic interventions, and informing surgical and rehabilitation planning. Historically, intradiscal pressure (IDP) provided one of the few internal in vivo measures of disc loading; more recently, telemetry, musculoskeletal (MS) modeling, finite element (FE) analysis, hybrid MS-FE approaches, dis...
Although deep learning models have improved individual PET analysis, image processing, and quantification tasks, end-to-end automation from raw DICOM ...
OBJECTIVES: The application of large language models (LLMs) to systematic review tasks is rapidly expanding, yet the transparency and methodological r...
BACKGROUND: Egypt's health financing is characterised by persistently high out-of-pocket (OOP) payments exceeding 50% of total health expenditure and ...
AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance d...
Personal health large language models (PH-LLMs) have rapidly evolved from research prototypes into consumer-facing, data-linked systems that support s...
BACKGROUND: COPD remains a leading cause of global morbidity and mortality, with acute exacerbations driving disease progression and healthcare utilis...
BACKGROUND: Large language models (LLMs) are being integrated into qualitative research processes, yet the scope, function, and reporting quality of t...
OBJECTIVE: To systematically characterise United States Food and Drug Administration (FDA) authorised urology-specific artificial intelligence (AI)-en...
Quantitative structure-activity relationship (QSAR) modeling underpins computational drug discovery, yet the factors governing model generalizability ...
OBJECTIVE: In emergency trauma care, artificial intelligence (AI) may aid fracture detection on radiographs, potentially reducing radiologists' worklo...
BACKGROUND: Online health information seeking (OHIS) has become a central component of chronic disease management within an increasingly interactive, ...
INTRODUCTION: Sepsis is a life-threatening condition in intensive care units (ICUs), where any delay in diagnosis and treatment can lead to organ dysf...
Large language models (LLMs) are starting to be coupled with brain-computer interfaces (BCIs) for assistive communication, but the resulting systems d...
BACKGROUND: The 2016 Comprehensive Addiction and Recovery Act amended the Child Abuse Prevention and Treatment Act (CAPTA), expanding requirements for...
INTRODUCTION: Loneliness and social isolation are critical public health issues linked to significant adverse health outcomes and increased healthcare...
Pyroelectric devices hold promise for thermal energy harvesting and sensing. While previous studies have focused on the intrinsic pyroelectric respons...
BACKGROUND: Alcohol is a group 1 carcinogen linked to seven cancers, yet awareness of this risk remains low in the United State. Identifying effective...
Drug safety assessment, particularly in the post-marketing setting, is especially vulnerable to analytic misjudgment because it relies on heterogeneou...