AIMC Topic: Machine Learning

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Association of the dietary index for gut microbiota with metabolic syndrome and its components combining interpretable machine learning algorithms.

Journal of health, population, and nutrition
BACKGROUND: Previous studies have emphasized the critical role of diet and gut microbiome in Metabolic syndrome (MetS). The dietary index for gut microbiota (DI-GM) represents a novel dietary index that effectively reflects the diversity of gut micro...

The effect of acetyl tributyl citrate on coronary heart disease: a comprehensive computational analysis.

BMC pharmacology & toxicology
BACKGROUND: Recent research suggests a link between acetyl tributyl citrate (ATBC) exposure and an increased risk of coronary heart disease (CHD).

Single cell and machine learning identify type II pneumocyte-derived biomarkers HN1/OCIAD2/SFTA2 for non-small cell lung cancer prognosis and immune regulation.

European journal of medical research
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the most prevalent malignancies and currently shows a poor clinical prognosis. Type II pneumocyte, as one of the main sources of cancer cells in NSCLC, is important to explore the molecular fun...

Online machine learning model for predicting delirium risk in elderly patients with chronic kidney disease: development and preliminary validation.

European journal of medical research
BACKGROUND: Delirium frequently complicates elderly chronic kidney disease (CKD) patients due to multifactorial vulnerability. Early detection in geriatric intensive care unit (ICU) settings is challenged by traditional assessments' communication def...

A machine learning-driven early warning system for cryptocaryoniasis in marine aquaculture.

Parasites & vectors
BACKGROUND: Disease outbreaks, particularly cryptocaryoniasis caused by the ciliate Cryptocaryon irritans, pose significant barriers to sustainable marine fish aquaculture, undermining productivity, profitability, and biosecurity. Despite its impact,...

Interpretable and reproducible machine learning model for coronary calcification and segment-level stenoses stratification on computed tomography angiography.

BMC medicine
BACKGROUND: Coronary computed tomography angiography (CCTA) is widely used as a first-line tool for diagnosing and managing coronary artery disease (CAD), and machine learning (ML)-based analysis shows promise for quantitative CAD assessment.

Early detection of at-risk health sciences students: a machine learning-based predictive study using midterm grades.

BMC medical education
BACKGROUND: Early identification of students at academic risk is critical in health sciences education, particularly in regions prioritizing healthcare workforce development. This study evaluated the application of established machine learning (ML) c...

Serum lipid metabolic characteristics and potential biomarkers in first-episode schizophrenia.

BMC psychiatry
BACKGROUND: Lipids play a vital role in health and disease, but changes to their circulating levels and the link with schizophrenia remains poorly characterized. This study aimed to investigate the pathological lipid profiles in patients with first-e...

Artificial intelligence-based diagnosis of diabetic kidney disease using urinary VOC biosensor data.

BMC nephrology
BACKGROUND: Diabetic kidney disease (DKD) remains a leading cause of chronic kidney disease worldwide. However, current diagnostic methods rely on indirect biomarkers or invasive renal biopsy. This study aimed to evaluate the feasibility of urinary v...

Perspectives on morphology, physiology, genetic polymorphism and machine learning in cucumber grafting under zinc toxicity.

BMC plant biology
BACKGROUND: Heavy metal contamination in agricultural soils disrupts plant growth and metabolism. Although zinc (Zn) is a necessary element, concentrations above 50 ppm can be toxic to plants. Grafting has emerged as a potential strategy to mitigate ...