DenseNet
2 papers1 finding
- Humans2
Associations
1Chronological age
upin humans1
1 study
Chronological age
upin humans1
DenseNet predicts chronological age in humans (r = 0.89; MAE = 7.26).
“BrainageR and DenseNet demonstrated the highest predictive accuracy (r = 0.83; 0.89) and lowest mean absolute errors (MAE = 5.94; 7.26).”
Humanshealthy comparison participantsbrain
Comparison of Brain Age Algorithms in Bipolar Disorder
bioRxiv (Cold Spring Harbor Laboratory)21 Nov 2025Preprint
Latest
13 in 12 monthsNeurotoxicology and Teratology
Differential sensitivity of MRI-based brain-age models to chronic noise exposure: an exploratory comparative study
Cross-sectional study of 108 peoplePopulations
European Journal of Radiology Artificial Intelligence
Hybrid deep learning time-to-event modeling of major adverse cardiovascular events using coronary artery calcium score scans
Cohort study of 1,950 peopleMajor adverse cardiovascular events
Research Square
Cardio Fusion: A Dual-Stream Regularized Fusion Architecture for Generalizable Cardiovascular Disease Prediction Under Dataset Heterogeneity
Preprint: computational studyCardiovascular disease
Journal of Bone and Mineral Metabolism
Comparison of dual-energy X-ray absorptiometry and lumbar radiographs using deep learning for osteoporosis diagnosis
Computational studyOsteoporosis
Frontiers in Endocrinology
AI-assisted segmentation-based fusion model integrating deep learning, radiomics, and clinical parameters for identifying coronary heart disease risk in patients with MAFLD
Cohort study of 1,515 peopleCoronary heart disease
arXiv
Weight and Height Estimation from a Single Human Image Captured in the Wild
Preprint: computational studyBiomarkers
Alzheimer's & Dementia
Deep learning-based MRI analysis reveals Lewy body co-pathology accelerates brain aging in Alzheimer's disease
Cohort study in peopleAlzheimer's disease
bioRxiv
Attention-Guided Multimodal Neuroimaging Fusion Network for Modeling Brain Aging Pattern
Preprint: computational studyBiomarkers
Journal of Advanced Research
Multidimensional integrative analysis unveils genetic architecture, risk factors, and health consequences of brain aging
Cohort study of 42,385 peopleBiomarkers
AAIC 2025 Abstract
Synergistic Neurodegeneration in Alzheimer's Disease with Lewy Body Co‐Pathology: Insights from Deep Learning and CSF α‐Synuclein Seed Amplification Assays
Cohort study of 4,355 peopleAlzheimer's disease