OBJECTIVES: Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess la...
Journal of cataract and refractive surgery
Dec 1, 2024
PURPOSE: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2024
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.
JAMA otolaryngology-- head & neck surgery
Dec 1, 2024
IMPORTANCE: Accurate, timely, and cost-effective methods for staging oropharyngeal cancers are crucial for patient prognosis and treatment decisions, but staging documentation is often inaccurate or incomplete. With the emergence of artificial intell...
Intervertebral disc degeneration (IDD) is a primary cause of low back pain and disability. Cellular senescence and apoptosis due to endoplasmic reticulum stress (ERS) are key in IDD pathology. Identifying biomarkers linked to ERS in IDD is crucial fo...
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Nov 27, 2024
BACKGROUND: Outcome prediction for live-donor kidney transplantation improves clinical and patient decisions and donor selection. However, the currently used models are of limited discriminative or calibration power and there is a critical need to im...
To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magnetic resonance (CMR) features based on machine learning algorithms. The study was a retrospective co...
To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease. In this single-center retrospective cohort study, cons...
To develop and validate an artificial intelligence (AI) diagnostic model for coronary artery disease based on facial photos. This study was a cross-sectional study. Patients who were scheduled to undergo coronary angiography (CAG) at Beijing Anzhen...
Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in available cohorts. We introduce "genome-wide association neural networks (GWANN)" a novel approach tha...
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