Publications
128
Citations
8,089
Est. group size
~2
Recurring co-author estimate
Active years
19
Publishing since 2008
Dong Hye Ye's research applies artificial intelligence and deep learning methods to medical imaging problems, including analysis of brain scans, retinal images, breast cancer histology, and CT/MRI data. Work spans developing new neural network architectures (such as graph-based and diffusion models) for tasks like disease classification, automated medical report generation, and studying brain structure-function relationships, often with applications to neurodevelopment and substance exposure. This is a good fit for students interested in AI methods applied to healthcare and medical image analysis.
Publication output has grown substantially in recent years, rising from roughly 5-11 papers per year in the late 2010s to about 15-20 per year from 2024 onward.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Early postnatal changes in thyroid-stimulating hormone and subsequent neurodevelopment in preterm infants
Frontiers in Endocrinology · 2026
- DiA-gnostic VLVAE: Disentangled Alignment-Constrained Vision Language Variational AutoEncoder for Robust Radiology Reporting with Missing Modalities
Proceedings of the AAAI Conference on Artificial Intelligence · 2026
- KOCOBrain: Kuramoto-Guided Graph Network for Uncovering Structure-Function Coupling in Adolescent Prenatal Drug Exposure
Open MIND · 2026
- Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images
arXiv (Cornell University) · 2026
- Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images
arXiv (Cornell University) · 2026
- KOCOBrain: Kuramoto-Guided Graph Network for Uncovering Structure-Function Coupling in Adolescent Prenatal Drug Exposure
arXiv (Cornell University) · 2026
- NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance Use Initiation Prediction from Longitudinal Functional Connectome
arXiv (Cornell University) · 2026
- Learning Structural-Functional Brain Representations through Multi-Scale Adaptive Graph Attention for Cognitive Insight
arXiv (Cornell University) · 2026
- Learning Structural-Functional Brain Representations through Multi-Scale Adaptive Graph Attention for Cognitive Insight
arXiv (Cornell University) · 2026
- NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance Use Initiation Prediction from Longitudinal Functional Connectome
arXiv (Cornell University) · 2026
- NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance use Initiation Prediction from Longitudinal Functional Connectome
2026
- Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging
arXiv (Cornell University) · 2026
- Learning Structural–Functional Brain Representations Through Multi–Scale Adaptive Graph Attention For Cognitive Insight
2026
- DREAM: Dynamic Retinal Enhancement with Adaptive Multi-modal Fusion for Expert Precision Medical Report Generation
arXiv (Cornell University) · 2026
- DREAM: Dynamic Retinal Enhancement with Adaptive Multi-modal Fusion for Expert Precision Medical Report Generation
arXiv (Cornell University) · 2026
- arXiv (Cornell University)×22
- Electronic Imaging×8
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition×4
- IEEE Transactions on Computational Imaging×3
- Analytical Chemistry×3
- Madhuri Nagare
Medicine · Purdue University West Lafayette
- Gregery T. Buzzard
Medicine · Purdue University West Lafayette
- Charles A. Bouman
Medicine · Purdue University West Lafayette
- Jeffrey Martin
Medicine · Indiana University
- Zachary Smith
Medicine · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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