BACKGROUND: Predicting in-hospital cardiac arrest (IHCA) is crucial for potentially reducing mortality and improving patient outcomes. However, most models, which rely solely on vital signs, may not comprehensively capture the patients' risk profiles...
OBJECTIVE: This study aimed to develop a prediction tool to identify abdominal aortic aneurysms (AAAs) at increased risk of rupture incorporating demographic, clinical, imaging, and medication data using artificial intelligence (AI).
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Dec 13, 2024
OBJECTIVE: The purpose of this study was to evaluate the effectiveness of a deep learning model (DLM) in improving the sensitivity of neurosurgery residents to detect intracranial aneurysms on CT angiography (CTA) in patients with aneurysmal subarach...
BACKGROUND: Novel circulating markers for the non-invasive staging of chronic liver disease (CLD) are in high demand. Although underutilized, extracellular matrix (ECM) components offer significant diagnostic potential. This study evaluates ECM-relat...
Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). H-NMR-based metabonomics data of the serum samples of patient...
BACKGROUND: Prediction models based on machine learning (ML) methods are being increasingly developed and adopted in health care. However, these models may be prone to bias and considered unfair if they demonstrate variable performance in population ...
BACKGROUND: In recent years, machine learning (ML)-based models have been widely used in clinical domains to predict clinical risk events. However, in production, the performances of such models heavily rely on changes in the system and data. The dyn...
PURPOSE: This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non-small cell lung cancer (NSCLC) using real-world data (RWD) and clinical trial data.
BACKGROUND: Snakebite envenoming is a serious condition that affects 2.5 million people and causes 81,000-138,000 deaths every year, particularly in tropical and subtropical regions. The World Health Organization has set a goal to halve the deaths an...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.