Li, Huating

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

Toll-like receptor-4 mediates obesity-induced non-alcoholic steatohepatitis through activation of X-box binding protein-1 in mice

Ye, D., Li, F. Y. L., Lam, K. S. L., Li, H., Jia, W., Wang, Y., Man, K., Lo, C. M., Li, X., & Xu, A. (2012) · Gut

Liver Disease Diagnosis and TreatmentLiver physiology and pathology

Cited by 206

Fibroblast growth factor 21 protects against acetaminophen-induced hepatotoxicity by potentiating peroxisome proliferator-activated receptor coactivator protein-1α-mediated antioxidant capacity in mice

Ye, D., Wang, Y., Li, H., Jia, W., Man, K., Lo, C. M., Wang, Y., Lam, K. S. L., & Xu, A. (2014) · Hepatology

Drug-Induced Hepatotoxicity and ProtectionFibroblast Growth Factor Research

Cited by 184

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

Risk assessment with gut microbiome and metabolite markers in NAFLD development

Leung, H., Long, X., Ni, Y., Qian, L., Nychas, E., Siliceo, S. L., Pohl, D., Hanhineva, K., Liu, Y., Xu, A., et al. (2022) · Science Translational Medicine

Gut microbiota and healthLiver Disease Diagnosis and Treatment

Cited by 152

Artificial intelligence for diabetes care: current and future prospects

Sheng, B., Pushpanathan, K., Guan, Z., Lim, Q. H., Lim, Z. W., Yew, S. M. E., Goh, J. H. L., Bee, Y. M., Sabanayagam, C., Sevdalis, N., et al. (2024) · The Lancet Diabetes & Endocrinology

Artificial Intelligence in Healthcare and EducationDiabetes Management and Research

Cited by 106