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Middle Aged
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Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes.
Cardiovascular diabetology
Jan 2, 2025
BACKGROUND: Prior studies have demonstrated an association between retinal vascular features and cardiovascular disease (CVD), however most studies have only evaluated a few simple parameters at a time. Our aim was to determine whether a deep-learnin...
Aged
Humans
Male
Diabetic Retinopathy
Cardiovascular Diseases
Decision Support Techniques
Predictive Value of Tests
Middle Aged
Heart Disease Risk Factors
Image Interpretation, Computer-Assisted
Photography
Retinal Vessels
Risk Assessment
Deep Learning
Prognosis
Time Factors
Female
Diabetes Mellitus, Type 2
Reproducibility of Results
Risk Factors
Predicting autoimmune thyroiditis in primary Sjogren's syndrome patients using a random forest classifier: a retrospective study.
Arthritis research & therapy
Jan 2, 2025
BACKGROUND: Primary Sjogren's syndrome (pSS) and autoimmune thyroiditis (AIT) share overlapping genetic and immunological profiles. This retrospective study evaluates the efficacy of machine learning algorithms, with a focus on the Random Forest Clas...
Weakly supervised deep learning-based classification for histopathology of gliomas: a single center experience.
Scientific reports
Jan 2, 2025
Multiple artificial intelligence systems have been created to facilitate accurate and prompt histopathological diagnosis of tumors using hematoxylin-eosin-stained slides. We aimed to investigate whether weakly supervised deep learning can aid in glio...
Gait-based Parkinson's disease diagnosis and severity classification using force sensors and machine learning.
Scientific reports
Jan 2, 2025
A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait signals using force sensors and machine learning approaches, is proposed in this study. Parkinson's disease is the primary neurodegenerative disorder...
Employing a low-code machine learning approach to predict in-hospital mortality and length of stay in patients with community-acquired pneumonia.
Scientific reports
Jan 2, 2025
Community-acquired pneumonia (CAP) is associated with high mortality rates and often results in prolonged hospital stays. The potential of machine learning to enhance prediction accuracy in this context is significant, yet clinicians often lack the p...
Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.
Nature communications
Jan 2, 2025
Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, w...
Machine learning for early detection and severity classification in people with Parkinson's disease.
Scientific reports
Jan 2, 2025
Early detection of Parkinson's disease (PD) and accurate assessment of disease progression are critical for optimizing treatment and rehabilitation. However, there is no consensus on how to effectively detect early-stage PD and classify motor symptom...
Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images.
Scientific reports
Jan 2, 2025
Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addre...
Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.
Nature communications
Jan 2, 2025
Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS),...
Performance analysis of a deep-learning algorithm to detect the presence of inflammation in MRI of sacroiliac joints in patients with axial spondyloarthritis.
Annals of the rheumatic diseases
Jan 2, 2025
OBJECTIVES: To assess the ability of a previously trained deep-learning algorithm to identify the presence of inflammation on MRI of sacroiliac joints (SIJ) in a large external validation set of patients with axial spondyloarthritis (axSpA).
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