AIMC Topic: Cohort Studies

Clear Filters Showing 1 to 10 of 1264 articles

Preoperative CT imaging and machine learning models for predicting ureteral access sheath placement success in non-stented patients with ureteral calculi: a retrospective cohort study.

World journal of urology
OBJECTIVE: This study aims to both develop and evaluate a predictive model for ureteral access sheath(UAS)placement success using preoperative CT-based 3D ureteral imaging and machine learning techniques. Specifically, it investigates the impact of u...

Predicting symptomatic intracranial hemorrhage after endovascular treatment of vertebrobasilar artery occlusion: PEACE score.

Journal of neurointerventional surgery
BACKGROUND: Current clinical decision tools for assessing the risk of symptomatic intracranial hemorrhage (sICH) in patients with vertebrobasilar artery occlusion (VBAO) who received endovascular treatment (EVT) have limited performance. This study d...

PRIME: an interpretable artificial intelligence model based on liquid biopsy improves prediction of progression risk in non-small cell lung cancer.

Military Medical Research
BACKGROUND: Despite the predictive impact of circulating tumor DNA (ctDNA) minimal residual disease (MRD), accurate prediction of failure risk after curative-intent treatments for early-stage or localized non-small cell lung cancer (NSCLC) patients t...

Development and Validation of an Interpretable Hemodynamics-Based Machine Learning Model for Predicting Cerebral Arteriovenous Malformation Rupture.

Translational stroke research
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...

cMeta-INR: cohort-informed meta-learning-based implicit neural representation for deformable registration-driven real-time volumetric MRI estimation.

Physics in medicine and biology
Rapid and accurate reconstruction of high-quality three-dimensional magnetic resonance (MR) images from undersampled-space data with variable sampling patterns remains a challenge due to limited available information and the need to preserve rich ana...

Association of Brain Age With Physical Disability and Cognitive Impairment in People With Multiple Sclerosis of the Same Age.

Neurology
BACKGROUND AND OBJECTIVES: The brain-predicted age difference (brain-PAD) is a novel marker of neurodegeneration in multiple sclerosis (MS). Brain-PAD has been associated with clinical disability in heterogeneous MS patient cohorts of varying ages an...

Biological age threshold is associated with symptomatic knee osteoarthritis risk in chinese adults: Insights from machine learning analysis of a national cohort.

PloS one
BACKGROUND: Symptomatic knee osteoarthritis (KOA) imposes a substantial global health and economic burden. Although chronological age (CA) is a key risk factor, it poorly reflects interindividual aging heterogeneity. Biological age (BA), which is qua...

Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) and unstable angina (UA) often coexist in clinical practice, constituting a high-risk cardiovascular phenotype with a markedly increased incidence of major adverse cardiovascular even...

The effects of physical activity on diabetic retinopathy in type 2 diabetes using automated vascular analysis: a cohort study.

Journal of global health
BACKGROUND: Evidence regarding the association between physical activity (PA) and diabetic retinopathy (DR) remains inconsistent. Furthermore, its effects on retinal vessel diameters in type 2 diabetes are not well established. We aimed to investigat...

Identification of PIWI-interacting RNAs based models for lung adenocarcinoma early detection: a multicenter cohort study.

Molecular biomedicine
Early detection of lung adenocarcinoma (LUAD) remains a major clinical challenge despite the widespread application of low-dose computed tomography (LDCT). Circulating PIWI-interacting RNAs (piRNAs), characterized by tumor-specific expression and hig...