Latest AI and machine learning research in risk management for healthcare professionals.
Real-world ocular imaging datasets are essential for advancing research in artificial intelligence (AI), autonomous disease screening, and clinical decision support. The Primary Eye Care dataset is a large-scale collection of de-identified retinal imaging data from routine optometric care, made available through the Institute for Digital Health (IDHea)—a secure research platform established by Top...
Large language models (LLMs) have emerged as powerful tools for sentiment analysis in healthcare, offering potential advantages in capturing contextual information and semantic relationships in complex medical text. Healthcare sentiment analysis presents unique challenges due to domain-specific terminology, privacy regulations, and the nuanced nature of patient experiences. This systematic review ...
Integrated digital diagnostics can support complex surgeries in many anatomic sites, and brain tumour surgery represents one of the most complex cases...
Advancements in artificial intelligence (AI) are revolutionising the healthcare sector, but challenges exist in AI adoption and its long-term use. Thi...
Loneliness is a significant public health concern that affects millions of people worldwide, particularly older adults. With advancements in artificia...
Artificial intelligence (AI) technologies are increasingly being integrated into mental health interventions, but their impact on user experience and ...
Artificial Intelligence (AI) is rapidly changing the legal landscape of radiology. Results from a previous experiment suggested that providing AI erro...
Target Trial Emulation (TTE) has emerged as a rigorous framework for causal inference using observational data, but its application in hypertension re...
Large language models (LLMs) demonstrate human-level performance in three key domains: linguistic understanding, knowledge-based reasoning, and comple...
Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of mental illness. Since delay in initiation of ECT can have detrim...
Delirium is a serious and common condition in hospitalized patients, associated with increased morbidity, mortality, and healthcare costs. Early detec...
Mindfulness-based interventions (MBIs) have gained significant recognition as effective approaches for promoting mental health and well-being. With ra...
Diabetes represents an emerging global health crisis, with lower-middle-income countries experiencing a fast growth in prevalence. Diabetes care in th...
Fetal MRI is increasingly being employed in the diagnosis of fetal lung anomalies and segmentation-derived total fetal lung volumes are used as one of...
Non-communicable diseases (NCDs) account for ∼71% of all deaths globally, including 15 million premature deaths each year (deaths between 30-69 years ...
Manual assignment of International Classification of Diseases (ICD) codes is error-prone. Transformer-based large language models (LLMs) have been pro...
Educating clinicians about Artificial Intelligence (AI) is an urgent need(1) as the UK General Medical Council (GMC) places liability with practitione...
Artificial intelligence (AI) is increasingly embedded in clinical trials, yet poor reproducibility remains a critical barrier to trustworthy and trans...
Artificial intelligence (AI) has potentially shown promise in interpreting ultrasound imaging through flexible pattern recognition and algorithmic lea...
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by diverse presentations and a strong genetic component. Environmental ...