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Machine learning-based CAD detection using integrated ECG and PCG parameter features.

Biomedical physics & engineering express
The combined analysis of electrocardiogram (ECG) and phonocardiogram signals(PCG) has demonstrated significant potential in the non-invasive detection of coronary artery disease (CAD). The efficacy of combining cardiac pathological parameters such as...

Stimulus Contingency and Task Context Encoding within the Anterior Cingulate-Amygdala-Cerebellum Associative Learning Network.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Cerebellum (CB) interactions with forebrain systems contribute to learning cognitive and motor tasks, but the nature of these interactions is unknown. Trace eyeblink conditioning (EBC) is an excellent associative learning paradigm for examining inter...

Explainable mortality prediction models incorporating social health determinants and physical frailty for heart failure patients.

PloS one
There is limited evidence on how social determinants of health (SDOH) and physical frailty (PF) influence mortality prediction in heart failure (HF), particularly for in-hospital, 90-day, and 1-year outcomes. This study aims to develop explainable ma...

Lung and abdominal ultrasound accuracy for tuberculosis: An Indian prospective cohort study.

PloS one
BACKGROUND: Tuberculosis (TB) diagnosis remains a challenge, particularly in low-resource settings. Point-of-care ultrasound (POCUS) has shown promise, but most studies focus on HIV-infected populations. In the case of TB, data on lung ultrasound (LU...

AI-driven analysis of diabetes risk determinants in U.S. adults: Exploring disease prevalence and health factors.

PloS one
BACKGROUND: Diabetes remains a major public health concern in the United States, with a complex interplay of behavioral, demographic, and clinical risk factors. This study aims to identify the three best-performing machine learning models for diabete...

Diagnostic PANoptosis-related genes in acute kidney injury: bioinformatics, machine learning, and validation.

Annals of medicine
BACKGROUND: Acute kidney injury (AKI) is a prevalent and life-threatening condition characterized by abrupt renal function decline and subsequent inflammatory cascades. PANoptosis has emerged as a significant contributor to the pathophysiology of AKI...

Multi-level validation of high expression of PLAUR, FOSL2, and SLC11A1 in aortic dissection and their clinical implications.

International immunopharmacology
Macrophages, pivotal orchestrators of the immune system, are integral to the initiation of specific immune responses and exert profound influence on the pathogenesis, progression, and therapeutic landscape of aortic dissection (AD). Leveraging the pr...

CLAW-MRM: omprehensive ipidomics utomation orkflow for ultiple eaction onitoring Using Large Language Models.

Analytical chemistry
Lipidomic profiling generates vast datasets, making manual annotation and trend interpretation complex and time-intensive. The structural and chemical diversity of the lipidome further complicates the analysis. While existing tools support targeted l...

Differentiation of benign and malignant oral lesions through surface texture analysis and SVM modeling.

Clinical oral investigations
OBJECTIVES: To evaluate the diagnostic potential of surface texture features extracted from clinical images in objectively differentiating benign from malignant oral lesions, and to validate classification performance of a Support Vector Machine (SVM...

Overcoming Site Variability in Multisite fMRI Studies: an Autoencoder Framework for Enhanced Generalizability of Machine Learning Models.

Neuroinformatics
Harmonizing multisite functional magnetic resonance imaging (fMRI) data is crucial for eliminating site-specific variability that hinders the generalizability of machine learning models. Traditional harmonization techniques, such as ComBat, depend on...