AIMC Topic: Middle Aged

Clear Filters Showing 481 to 490 of 17155 articles

Multimodal Multitask Learning for Predicting Depression Severity and Suicide Risk Using Pretrained Audio and Text Embeddings: Methodology Development and Application.

JMIR medical informatics
BACKGROUND: Depression is a critical psychological disorder necessitating urgent assessment and treatment, given its strong association with increased suicide risk (SR). Effective management hinges on promptly identifying individuals with high depres...

Machine learning-enhanced direct mass spectrometry analysis of non-volatile breath metabolites for rapid and accurate lung cancer screening.

Analytical methods : advancing methods and applications
Breath analysis by direct mass spectrometry faces significant challenges due to the inherent complexities in sample collection, low analyte concentrations, and accurate compound identification. While current breath analysis primarily focuses on volat...

Predicting hypertension and identifying most important factors among married women in Bangladesh using machine learning approach.

PloS one
INTRODUCTION: Hypertension is a leading contributor to maternal and cardiometabolic morbidity in Bangladesh. We developed and interpreted machine-learning (ML) models to predict hypertension and rank associated factors among married women with the go...

Machine learning-driven risk stratification for distant metastasis in gastric cancer: A comparative study of clinical features and composite indices integrated models.

PloS one
OBJECTIVE: Distant metastasis (DM) of gastric cancer (GC) represents a significant health challenge due to its high mortality rates, necessitating advancements in early detection and management strategies. The objective of this study was to create a ...

Multi-omics and machine learning identify FN1 and ALDH2 as diagnostic biomarkers and therapeutic targets in early and late diabetic kidney disease.

Renal failure
Diabetic kidney disease (DKD), the leading cause of end-stage kidney disease worldwide, demands deeper molecular characterization to improve clinical management. This study employed an integrated multi-omics approach to identify stage-specific biomar...

Integrative Deep Learning of Genomic and Clinical Data for Predicting Treatment Response in Newly Diagnosed Epilepsy.

Neurology
BACKGROUND AND OBJECTIVES: Epilepsy is a common neurologic disorder. Although antiseizure medications (ASMs) are the first-line treatment, identifying the most effective ASM for each individual remains a trial-and-error process. Genetic variation may...

Non-linear association between Life's Essential 8 and diabetic retinopathy: mediating role of depression in US adults with diabetes.

BMC public health
BACKGROUND: Life's Essential 8 (LE8) is a comprehensive cardiovascular health (CVH) metric that is associated with chronic diseases. This study aimed to investigate the association between LE8 and diabetic retinopathy (DR) and the mediating role of d...

Comparing radiomics, deep learning, and fusion models for predicting occult pleural dissemination in patients with non-small cell lung cancer: a retrospective multicenter study.

BMC cancer
BACKGROUND: Occult pleural dissemination (PD) in non-small cell lung cancer (NSCLC) patients is likely to be missed on computed tomography (CT) scans, associated with poor survival, and generally contraindicated for radical surgery. This study aimed ...

The effects of combining anodal transcranial direct current stimulation with robot-assisted gait training on lower limb motor function and the motor cortex regulation of stroke patients.

Journal of neuroengineering and rehabilitation
BACKGROUND: The therapeutic effect and underlying mechanism of combining transcranial direct current stimulation (tDCS) with robot-assisted gait training (RAGT) for stroke patients remain unclear.

Comprehensive analysis of metabolic and molecular alterations in the blood of patients with Sjögren's syndrome based on untargeted metabolomics analysis.

BMC medical genomics
BACKGROUND: Sjögren's syndrome (SS) is a chronic autoimmune disorder marked by lymphocytic infiltration of exocrine glands, leading to xerostomia, keratoconjunctivitis sicca, and systemic involvement including fatigue, arthralgia, and visceral organ ...