Shi, Danli

Enhancement of the Performance of Large Language Models in Diabetes Education through Retrieval-Augmented Generation: Comparative Study

Wang, D., Liang, J., Ye, J., Li, J., Li, J., Zhang, Q., Hu, Q., Pan, C., Wang, D., Liu, Z., et al. (2024) · Journal of Medical Internet Research

Artificial Intelligence in Healthcare and EducationInformation Retrieval and Search Behavior

Cited by 76

Economic evaluation for medical artificial intelligence: accuracy vs. cost-effectiveness in a diabetic retinopathy screening case

Wang, Y., Liu, C., Hu, W., Luo, L., Shi, D., Zhang, J., Yin, Q., Zhang, L., Han, X., & He, M. (2024) · npj Digital Medicine

Retinal Imaging and AnalysisHealth Systems, Economic Evaluations, Quality of Life

Cited by 76

FFA-GPT: an automated pipeline for fundus fluorescein angiography interpretation and question-answer

Chen, X., Zhang, W., Xu, P., Zhao, Z., Zheng, Y., Shi, D., & He, M. (2024) · npj Digital Medicine

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 72

Unveiling the clinical incapabilities: a benchmarking study of GPT-4V(ision) for ophthalmic multimodal image analysis

Xu, P., Chen, X., Zhao, Z., & Shi, D. (2024) · British Journal of Ophthalmology

Artificial Intelligence in Healthcare and EducationOphthalmology and Visual Health Research

Cited by 63

Associations of ophthalmic and systemic conditions with incident dementia in the UK Biobank

Shang, X., Zhu, Z., Huang, Y., Zhang, X., Wang, W., Shi, D., Jiang, Y., Yang, X., & He, M. (2023) · British Journal of Ophthalmology

Dementia and Cognitive Impairment ResearchRetinal Diseases and Treatments

Cited by 56

Contrastive pre-training and linear interaction attention-based transformer for universal medical reports generation

Lin, Z., Zhang, D., Shi, D., Xu, R., Tao, Q., Wu, L., He, M., & Ge, Z. (2023) · Journal of Biomedical Informatics

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 39

ICGA-GPT: report generation and question answering for indocyanine green angiography images

Chen, X., Zhang, W., Zhao, Z., Xu, P., Zheng, Y., Shi, D., & He, M. (2024) · British Journal of Ophthalmology

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 36

A Systematic Review of Advances in AI-Assisted Analysis of Fundus Fluorescein Angiography (FFA) Images: From Detection to Report Generation

Yu, T., Shao, A., Wu, H., Su, Z., Shen, W., Zhou, J., Lin, X., Shi, D., Grzybowski, A., Wu, J., et al. (2025) · Ophthalmology and Therapy

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 23