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Automatically quantifying spatial heterogeneity of immune and tumor hypoxia environment and predicting disease-free survival for patients with rectal cancer.

Cancer immunology, immunotherapy : CII
Immunohistochemistry (IHC) remains the gold standard for evaluating protein expression in tumor microenvironment analysis. This approach hinders robust correlation analyses between spatial heterogeneity in the tumor microenvironment and clinical outc...

Integrated machine learning and single-cell analysis identify chromatin-remodeling gene signature for diagnosis and prognosis in nasopharyngeal carcinoma.

Clinical and experimental medicine
This study examines the function of chromatin-remodeling genes (CRGs) in nasopharyngeal carcinoma (NPC), with an emphasis on their potential as prognostic and diagnostic biomarkers. We examined gene expression information collected from multiple data...

Predicting distant metastasis in early-onset kidney cancer using machine learning: a SEER database study with external validation.

Clinical and experimental medicine
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 ...

Impact of imaging biomarkers from body composition analysis on outcome of endovascularly treated acute ischemic stroke patients.

Journal of neurointerventional surgery
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...

FormulationLAI: A physiology-based machine learning framework for accelerated development of long-acting injectable formulations.

Journal of controlled release : official journal of the Controlled Release Society
Long-acting injectables (LAIs) represent promising drug delivery platforms for chronic diseases management, but their clinical translation remains constrained by extremely long trial-and-error experiments (8-10 years), limited mechanism insights, and...

A novel deep learning system for STEMI prognostic prediction from multi-sequence cardiac magnetic resonance.

Science bulletin
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...

C-reactive protein-triglyceride glucose index in predicting three-vessel coronary artery disease risk: a retrospective study using machine learning approaches.

Annals of medicine
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...

Variation in the efficiency of English general practices and associated factors: A cross-sectional study of 5069 general practices.

The European journal of general practice
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.

Machine learning combined with body composition predicts surgical difficulty in mid-low rectal cancer surgery.

Annals of medicine
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...

Effect of upper-limb robot-assisted therapy combined with pneumatic gloves on upper limb function in young and middle-aged stroke patients: a pilot randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: This study aimed to evaluate the effects of an end-effector-type upper-limb robot-assisted therapy (UL-RAT) combined with pneumatic gloves (PGs) on improving upper limb function in young and middle-aged stroke patients.