AIMC Topic: Male

Clear Filters Showing 861 to 870 of 27433 articles

Minimally invasive detection of early-stage opisthorchiasis-associated cholangiocarcinoma using label-free surface-enhanced Raman spectroscopy (SERS) of hamster serum.

PloS one
BACKGROUND: Cholangiocarcinoma (CCA) is a deadly cancer often detected late. Current diagnostic methods, such as ultrasound and invasive biopsies, have limitations; there is a critical need for a rapid, minimally invasive and effective strategy for t...

Comparison of serum lactate and lactate-derived ratios as prognostic biomarkers in pediatric dengue shock syndrome using supervised machine learning models.

PloS one
BACKGROUND: Dengue shock syndrome (DSS), with critical complications encompassing mechanical ventilation (MV), dengue-associated acute liver failure (PALF), and encephalitis, is associated with high mortality in children. Although serum lactate is a ...

Machine learning reveals distinct T-cell receptor clusters in plasma cell dyscrasias compared to healthy controls.

PloS one
T-cell receptor (TCR) repertoire diversity has been implicated in the progression and prognosis of multiple myeloma (MM). This study aimed to evaluate the association between T-cell clonality, immune response, and clinical outcomes in patients with p...

Deciphering lactate/lactylation networks in AML: integrated scRNA-seq and transcriptomics reveal functions and prognostic model.

BMC cancer
Acute myeloid leukemia (AML) exhibits pronounced heterogeneity, necessitating deep molecular characterization for precision therapy. Lactate metabolism and histone lactylation, influencing tumor biology via epigenetic regulation and immune microenvir...

Development of an explainable machine learning asthma prediction model using serum brominated flame retardants in a national population.

Clinical and experimental medicine
We aimed to explore the association of serum brominated flame retardant (BFR) metabolites and mixture profiles with asthma risk among US adults. Data were sourced from the National Health and Nutrition Examination Survey (NHANES), 1999-2023. Four mac...

Development of a machine learning-based prediction model for acute kidney injury associated with respiratory failure in the intensive care unit.

Clinical and experimental medicine
Acute kidney injury (AKI) is a frequent and severe complication in intensive care unit (ICU) patients with respiratory failure, associated with high mortality, prolonged hospitalization, and substantial healthcare burden. Conventional risk scores, su...

The CT-based deep learning model outperforms traditional anatomical classification models in preoperatively predicting complications and risk grade in partial nephrectomy.

World journal of urology
PURPOSE: A deep learning model integrating CT radiomics and clinical features was developed to predict perioperative complications and risk grade in patients undergoing partial nephrectomy, and was compared to traditional anatomical classification mo...

Identification of key diagnostic and prognostic biomarkers for aortic valve stenosis with coronary artery disease through immunological profiling integrating proteomics, single-cell sequencing, and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Aortic valve stenosis with coronary artery disease (AS-CAD) represents a common yet complex cardiovascular comorbidity, characterized by multifactorial pathogenesis and a lack of specific serum biomarkers. These limitations hinder early d...

Etiology-Agnostic Diagnosis of Early Myocardial Ischemia via AI-Driven Label-Free Spectral Histopathology.

Analytical chemistry
Myocardial ischemia is a core pathological mechanism in diverse fatal diseases and can be triggered by multiple factors. Diagnosing early myocardial ischemia (EMI) caused by nontraditional factors (e.g., drugs or stress) remains challenging due to su...

Whole-genome sequencing reveals individual and cohort level insights into chromosome 9p syndromes.

Genome medicine
BACKGROUND: Previous genomic efforts on chromosome 9p deletion and duplication syndromes have utilized low-resolution strategies (i.e., karyotypes, chromosome microarrays). These studies have provided important initial insights into these syndromes. ...