Wu, Liang

A deep learning system for detecting diabetic retinopathy across the disease spectrum

Dai, L., Wu, L., Li, H., Cai, C., Wu, Q., Kong, H., Liu, R., Wang, X., Hou, X., Liu, Y., et al. (2021) · Nature Communications

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 620

A deep learning system for predicting time to progression of diabetic retinopathy

Dai, L., Sheng, B., Chen, T., Wu, Q., Liu, R., Cai, C., Wu, L., Yang, D., Hamzah, H., Liu, Y., et al. (2024) · Nature Medicine

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 339

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

Guan, Z., Li, H., Liu, R., Cai, C., Liu, Y., Li, J., Wang, X., Huang, S., Wu, L., Liu, D., et al. (2023) · Cell Reports Medicine

Artificial Intelligence in Healthcare and EducationDiabetes Management and Research

Cited by 287

Integrated image-based deep learning and language models for primary diabetes care

Li, J., Guan, Z., Wang, J., Cheung, C. Y., Zheng, Y., Lim, L.-L., Lim, C. C., Ruamviboonsuk, P., Raman, R., Corsino, L., et al. (2024) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 250

Fibroblast growth factor 21 increases insulin sensitivity through specific expansion of subcutaneous fat

Li, H., Wu, G., Fang, Q., Zhang, M., Hui, X., Sheng, B., Wu, L., Bao, Y., Li, P., Xu, A., et al. (2018) · Nature Communications

Fibroblast Growth Factor ResearchAdipokines, Inflammation, and Metabolic Diseases

Cited by 178