AIMC Topic: Middle Aged
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Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods.
Renal failure
Jun 23, 2025
BACKGROUND: Chronic Kidney Disease (CKD) affects approximately 697.5 million people worldwide. Volatile organic compounds (VOCs) are emerging as potential risk factors, but their complex relationships with CKD may be underestimated by traditional lin...
Sleep disturbances and PTSD: identifying baseline predictors of insomnia response in an intensive treatment programme.
European journal of psychotraumatology
Jun 23, 2025
This study examined whether baseline demographic and clinical variables could predict clinically significant reductions in insomnia symptoms among veterans receiving a 2-week Cognitive Processing Therapy (CPT)-based intensive PTSD treatment programm...
Enhancing MRI efficiency in musculoskeletal examinations: Impact of optimized facility design and workflow optimization efforts.
European journal of radiology
Jun 23, 2025
BACKGROUND: To assess the workflow efficiency of an optimized MRI facility design compared to conventional facilities.
Extracting critical clinical indicators and survival prediction of lung cancer from pathology reports using large language models.
Computers in biology and medicine
Jun 23, 2025
Lung cancer remains the leading cause of cancer deaths in many developed countries, primarily due to late-stage diagnosis. Histopathology, the gold standard for diagnosis, often results in semi-structured pathological reports containing complex infor...
Biomarker risk stratification with capsule sponge in the surveillance of Barrett's oesophagus: prospective evaluation of UK real-world implementation.
Lancet (London, England)
Jun 23, 2025
BACKGROUND: Endoscopic surveillance is the clinical standard for Barrett's oesophagus, but its effectiveness is inconsistent. We have developed a test comprising a pan-oesophageal cell collection device coupled with biomarkers to stratify patients in...
[Incidental pulmonary nodules on CT imaging: what to do?].
Nederlands tijdschrift voor geneeskunde
Jun 23, 2025
Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage) lung cancers without any signs or symptoms. These incidental findings can be solid lesions or ground glass lesions that may be solitary or multiple. ...
Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with "double invasion" for personalized patient care.
European journal of medical research
Jun 23, 2025
OBJECTIVE: To develop and validate a machine learning framework combined with a nomogram for predicting recurrence after radical gastrectomy in patients with vascular and neural invasion.
Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction.
BMC nephrology
Jun 23, 2025
OBJECTIVE: IgA nephropathy (IgAN) is the most common form of glomerulonephritis worldwide, characterized by immune complex deposition in the glomerular mesangium, leading to mesangial hypercellularity, persistent microhematuria, proteinuria, and prog...
Inflammation-related 5-hydroxymethylation signatures as markers for clinical presentations of coronary artery disease.
Cardiovascular diabetology
Jun 23, 2025
BACKGROUND: Coronary angiography remains the gold standard for diagnosing coronary artery disease (CAD), but its invasive nature limits its applicability for widespread screening. Identifying non-invasive molecular markers could improve CAD classific...
Coronary Artery Disease
Inflammation Mediators
5-Methylcytosine
Humans
Risk Assessment
Severity of Illness Index
Non-ST Elevated Myocardial Infarction
Epigenesis, Genetic
DNA Methylation
Reproducibility of Results
Machine Learning
Predictive Value of Tests
Inflammation
Aged
Cell-Free Nucleic Acids
Biomarkers
ST Elevation Myocardial Infarction
Male
Prognosis
Middle Aged
Female
Artificial intelligence and the wellbeing of workers.
Scientific reports
Jun 23, 2025
This study explores the relationship between artificial intelligence (AI) and workers' well-being and health using longitudinal survey data from Germany (2000-2020). Using a measure of occupational exposure to AI, we explore an event study design and...
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