Clinica chimica acta; international journal of clinical chemistry
Jun 15, 2025
BACKGROUND: The erythrocyte sedimentation rate (ESR) is a traditional marker of inflammation, valued for its simplicity and low cost but limited by unsatisfactory specificity and sensitivity. This study evaluated the equivalence of ESR measurements o...
BACKGROUND: Cadmium (Cd) contamination in soils is a pressing environmental issue due to its toxicity and persistence. Given the diverse geological formations and intensive agricultural activities in Ireland, understanding the distribution and source...
Staphylococcus aureus (S. aureus) is the leading risk factor for food safety and human health. Herein, a novel wavelength-selective machine learning -driven adaptive strand exchange amplification (SEA)/SERS biosensor was developed for rapid detection...
Non-suicidal self-injury (NSSI) in adolescent girls is a critical predictor of subsequent depression and suicide risk, yet current tools lack both accuracy and clinical interpretability. We developed the first explainable machine learning model integ...
Coriander is a widely used spice, valued for its flavor, aroma, and nutritional benefits in various cuisines and food products. However, adulteration, such as the addition of sawdust, poses significant risks to food safety and authenticity. This stud...
This study utilized data from the 2020 wave of the China Health and Retirement Longitudinal Study database, selecting 4322 participants aged 60 and above as the study sample. Important predictors of depression in older adults with functional disabili...
Airborne microplastics (MPs) pose significant respiratory and systemic health risks upon inhalation; however, current assessment methods remain inadequate. This study integrates breathomics and transcriptomics to establish a non-invasive approach for...
The domains of food safety, quality, and nutrition are inundated with complex datasets. Machine learning (ML) has emerged as a powerful tool in food science, offering fast, accessible, and effective solutions compared with conventional methods. This ...
BACKGROUND: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder...
BACKGROUND: Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence i...
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