Latest AI and machine learning research in surveillance for healthcare professionals.
Effective monitoring of CO2 leaks from carbon capture and storage (CCS) sites is vital to mitigate environmental risks, including soil acidification and ecosystem disruption. This study presents a novel, sustainable biosensor based on betanin from Beta vulgaris (beetroot) extract for pH-responsive colorimetric detection of soil CO2 leakage, coupled with smartphone imaging for quantitative analysis...
INTRODUCTION: Advances in natural language processing (NLP) technologies have gained prominence for extracting relevant clinical information. Savana is a platform capable of analyzing free-text data and interpreting the content of electronic health records (EHRs). OBJECTIVE: To validate the results obtained through NLP by Savana from data of patients with prostate cancer (PC) included in active su...
INTRODUCTION: Focal therapy (FT) has emerged as an intermediate therapeutic strategy between active surveillance (AS) and radical treatments for the m...
BACKGROUND AND OBJECTIVE: White blood cells (WBCs) are key biomarkers of immune status, but current monitoring still relies on intermittent blood samp...
OBJECTIVE: To evaluate the diagnostic accuracy and workflow efficiency of BioticsAI-anatomyUNet-0.1-2022 software in identifying 18 standard fetal ana...
The global burden of hepatocellular carcinoma (HCC) has shifted from viral to nonviral etiologies. However, successful antiviral therapy does not full...
PURPOSE: To develop and validate a neural network-based Kid's Listening Performance Checklist (KLiP) for early identification of listening difficultie...
OBJECTIVE: This narrative review synthesizes machine learning (ML) applications across the stroke and post-stroke continuum from acute imaging and dia...
OBJECTIVES: To systematically review the evidence on the cost-effectiveness of artificial intelligence (AI) interventions for diagnostic imaging in ra...
BACKGROUND: Asthma is the most common chronic disease in children. Suboptimal asthma control is prevalent and causes significant health care costs. El...
BACKGROUND: The aim of this study was to construct a machine learning (ML) model to predict the effect of dietary antioxidants on cardiovascular-arthr...
BACKGROUND: A 24-hour urine collection is central to the metabolic evaluation and prevention of nephrolithiasis. Despite its widespread use, methodolo...
Prostate cancer remains a major global burden; diagnostic pathways rely on prostate-specific antigen (PSA), multiparametric magnetic resonance imaging...
BACKGROUND: Botulism is a rare but potentially fatal illness caused by botulinum neurotoxin, with outbreaks reported globally in humans, animals, and ...
Liver tumor diagnosis relies heavily on imaging, and the liver imaging reporting and data system (LI-RADS) provides a structured framework for evaluat...
BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...
An increasing number of Artificial intelligence (AI) and machine learning (ML) models are being developed to predict radiation-induced toxicities (RIT...
BACKGROUND: Delirium is a common complication following cardiac surgery and significantly affects patient prognosis and quality of life. Recently, the...
BACKGROUND: Effective cancer symptom management significantly impacts patient outcomes and quality of life. While Clinical Decision Support Systems sh...
BACKGROUND: Oral health is vital for children's overall well-being. Parents play a critical role in shaping children's oral health through preventive ...