Area of research
Cancer Research · Artificial Intelligence
Research interest
Research focused on Type 2 diabetes and Artificial intelligence, with related work in Glycemic, Glaucoma, Epigenetics. Notable publications include 'Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images', 'A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics', and 'Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial'.
Current progress and open challenges for applying artificial intelligence across the in vitro fertilization cycle
Self-improving generative foundation model for synthetic medical image generation and clinical applications
Concepts and applications of digital twins in healthcare and medicine
Transformer-based AI technology improves early ovarian cancer diagnosis using cfDNA methylation markers
A generalized AI system for human embryo selection covering the entire IVF cycle via multi-modal contrastive learning
Accurate prediction of myopic progression and high myopia by machine learning
A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial
Biomarkers of ageing: Current state‐of‐art, challenges, and opportunities
A deep-learning system predicts glaucoma incidence and progression using retinal photographs
Lipid metabolism dysfunction induced by age-dependent DNA methylation accelerates aging
Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images
Cold-Inducible Klf9 Regulates Thermogenesis of Brown and Beige Fat