Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
BACKGROUND: Conventional cytogenetic analysis remains central to the diagnosis and risk stratification of hematological malignancies but is constrained by labor-intensive workflows, inter-observer variability, and sensitivity to image quality. Although artificial intelligence (AI) approaches have been proposed for individual analytical tasks, clinically integrated, end-to-end pipelines aligned wit...
Large language models (LLMs), built on transformer architecture, have emerged as a fundamental tool in natural language processing and contextual reasoning, and have been extended to multimodal data interpretation, which has been termed large multimodal models (LMMs). Radiology as a medical discipline, having undergone full digital transformation over the past two decades, is uniquely positioned a...
BACKGROUND: The internet, social media, and digital health tools have transformed access and receipt of medicines information (MI), complementing or r...
Analytical chromatography is a cornerstone of modern science, yet a growing proportion of its literature risks contributing little genuine innovation....
Timely activation of massive hemorrhage protocols (MHP) is critical to prevent exsanguination and improve survival in trauma patients. Current clinica...
OBJECTIVE: To synthesise how studies evaluating AI-based caries detection on bitewing radiographs report evidence relevant to real-world clinical use ...
BACKGROUND: Artificial intelligence (AI)-based conversational tools are rapidly expanding within mental health care as a means of increasing access an...
Prostate MRI is central to the diagnostic pathway for prostate cancer (PCa), reducing unnecessary biopsies, improving the detection of clinically sign...
UNLABELLED: Osteoporosis is a major and growing health concern in the Asia-Pacific region, y et it remains widely underdiagnosed and undertreated due ...
Human rights research increasingly employs computational text analysis, but existing datasets provide either document-level aggregations or event-leve...
BACKGROUND: As a standalone parameter, the wound surface area can be used to describe a wound in medical records; however, changes in the wound surfac...
BACKGROUND: People who are incarcerated face significantly higher health risks than the general population, yet deaths in custody remain underreported...
Patch-wise learning is a common strategy for training neural networks on large-scale dense prediction problems, yet existing approaches assume uniform...
Population-based diabetic retinopathy (DR) screening requires diagnostic strategies that optimize clinical utility by balancing missed disease against...
BACKGROUND AND OBJECTIVES: Transparent and complete reporting in scientific papers is important for interpretation of study results and for downstream...
INTRODUCTION: Quality management systems are essential in clinical laboratories to ensure optimal operational output. However, report generation still...
BACKGROUND: Artificial intelligence (AI), including large language models (LLMs), is increasingly integrated into systematic review (SR) workflows. AI...
BACKGROUND: Reperfusion therapy, including thrombolysis and thrombectomy, is crucial for ischaemic stroke treatment. However, patient outcomes often r...
This study aimed to optimise the balance between participant burden and algorithm performance for predicting high-risk moments in a smoking cessation ...
To systematically evaluate the diagnostic accuracy of artificial intelligence (AI) models in periapical radiography for detection, classification, and...