6 papers
GlaKG: A Biomarker-Centric Fundus Knowledge Graph for Explainable Glaucoma Diagnosis and Risk Assessment
Cheng Huang, Jia Zhang, Yi Jiang +7
Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer little clinical interpretabilit…
GlaBoost: A Multimodal Structured Framework for Glaucoma Risk Stratification
Cheng Huang, Zeyu Han, Weizheng Xie +4
Early and accurate glaucoma detection is critical to prevent irreversible vision loss, yet existing AI methods often rely on unimodal inputs and lack interpretability. We present G…
Tibetan Language and AI: A Comprehensive Survey of Resources, Methods and Challenges
Cheng Huang, Nyima Tashi, Fan Gao +19
Tibetan, one of the major low-resource languages in Asia, presents unique linguistic and sociocultural characteristics that pose both challenges and opportunities for AI research.…
Automated Glaucoma Report Generation via Dual-Attention Semantic Parallel-LSTM and Multimodal Clinical Data Integration
Cheng Huang, Weizheng Xie, Zeyu Han +5
Generative AI for automated glaucoma diagnostic report generation faces two predominant challenges: content redundancy in narrative outputs and inadequate highlighting of pathologi…
X-GAN: A Generative AI-Powered Unsupervised Model for Main Vessel Segmentation of Glaucoma Screening
Cheng Huang, Weizheng Xie, Tsengdar J. Lee +4
Structural changes in main retinal blood vessels serve as critical biomarkers for the onset and progression of glaucoma. Identifying these vessels is vital for vascular modeling ye…
GlaLSTM: A Concurrent LSTM Stream Framework for Glaucoma Detection via Biomarker Mining
Cheng Huang, Weizheng Xie, Tsengdar Lee +3
Glaucoma is a complex group of eye diseases marked by optic nerve damage, commonly linked to elevated intraocular pressure and biomarkers like retinal nerve fiber layer thickness.…