Patients with early-onset kidney cancer (EOKC) face a marked decline in prognosis after distant metastasis, yet the accuracy of current predictive methods remains limited. This study aims to develop a predictive model using multiple machine learning ...
Journal of neurointerventional surgery
Nov 18, 2025
BACKGROUND: We investigate the association of imaging biomarkers extracted from fully automated body composition analysis (BCA) of computed tomography (CT) angiography images of endovascularly treated acute ischemic stroke (AIS) patients regarding an...
Recent advances in spatial transcriptomics (ST) have significantly enhanced our understanding of tissue structure and intercellular interactions. However, existing methods for spatial domain identification and cell type deconvolution still face chall...
ST-elevation myocardial infarction (STEMI) remains a leading cause of cardiovascular morbidity and mortality worldwide, and accurate early risk stratification is critical for implementing precision therapies in clinical practice. However, existing cl...
BACKGROUND: Three-vessel coronary artery disease (TVD) is a severe subtype of coronary heart disease, strongly associated with inflammation and metabolic dysfunction. The C-reactive protein-triglyceride glucose index (CTI), an integrated measure of i...
The European journal of general practice
Nov 17, 2025
BACKGROUND: Healthcare demand in English general practice exceeds supply, necessitating practice efficiency. To our knowledge, no study has explored factors associated with practice efficiency in England using a quality-adjusted output.
BACKGROUND: Accurate prediction of pregnancy outcomes in assisted reproductive technology (ART) remains a clinical challenge due to the complexity and heterogeneity of IVF/ICSI cycles. Existing models often focus on isolated treatment stages and rely...
BACKGROUND: This study sought to identify critical body composition characteristics associated with surgical difficulty in Laparoscopic Total Mesorectal Excision (LaTME) and to develop and validate an interpretable machine learning model using body c...
OBJECTIVE: To develop and validate an interpretable delta ultrasound radiomics model for predicting live birth following single vitrified-warmed blastocyst transfer (SVBT).
BACKGROUND: Accurate quantification of the Ki-67 proliferation index is essential for breast cancer prognosis and treatment planning. Current automated methods, including classical and deep learning approaches based on cell detection or segmentation,...
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