IEEE transactions on bio-medical engineering
Nov 1, 2025
Accurate segmentation of prostate tumors from multi-modal magnetic resonance (MR) images is crucial for the diagnosis and treatment of prostate cancer. However, the robustness of existing segmentation methods is limited, mainly because these methods ...
BACKGROUND: Low bone mineral density (BMD) is a common age-related condition that elevates the risk of fractures and mortality. Machine learning (ML) techniques offer a promising approach for early prediction using readily available clinical, biochem...
FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Oct 31, 2025
Protein arginine methylation was a common post-translational modification, playing a key role in many biological processes and disease. But the regulatory mechanisms of protein arginine methyltransferases (PRMTs) in cancer were not well understood. T...
Clinical chemistry and laboratory medicine
Oct 27, 2025
OBJECTIVES: Use of machine learning (ML) in diagnostics offers promise to optimise interpretation of laboratory data and guide clinical decision-making. For this, ML-based outputs should provide robustly reproducible results at least as good as the u...
Age-related hearing loss (HL) and sarcopenia (ARS) are prevalent geriatric syndromes sharing common risk factors. This study aimed to identify shared biomarkers and elucidate convergent pathogenic mechanisms. Transcriptomic datasets were obtained fro...
Acute kidney injury (AKI) is a serious condition characterized by a rapid decline in renal function, leading to severe complications. Recent findings suggest that cuproptosis-related genes (CuRGs) influence AKI mechanisms. This study investigated CuR...
The aim of this study was to investigate the relationship between serum ultrasensitive C-reactive protein (hs-CRP) levels and stroke incidence and to assess its potential role in decision-making for thrombolytic therapy in stroke. Given that hs-CRP i...
The incidence of hepatocellular carcinoma (HCC) has risen significantly in recent years, while current diagnostic and therapeutic approaches remain suboptimal. This study aimed to identify novel biomarkers and therapeutic targets to improve early det...
This study aims to identify angiogenesis-associated genes (AAGs) in endometriosis (EM) by integrating bioinformatics analysis with machine learning, and to investigate their underlying mechanisms. Differentially expressed genes (DEGs) were screened f...
This study aimed to predict mortality in cancer patients diagnosed with COVID-19 using machine learning (ML) algorithms and identify the clinical and laboratory parameters associated with mortality. Demographic, clinical, and laboratory data of cance...
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