- GH164
- 4825
- danli.shi@polyu.edu.hk
- Dr Shi's research interests include digital health in ophthalmology, generative AI, multimodality AI, and the integration of AI into clinical practice.
ORCID ID
SCOPUS IDBiography
Dr Shi is an ophthalmologist with a keen interest in artificial intelligence. She undertook her medical training at Shanghai Jiao Tong University School of Medicine (BS and MS degrees) and obtained a doctorate at Sun Yat-sen University in 2022. She has a strong research interest in artificial intelligence algorithm development and its translation into clinical practice.
Research Overview
Dr Shi’s main research interests are digital biomarkers of the eye and multimodality AI. Her novel application of cross-modality framework in eye research has attracted collaborative research in China and overseas.
Education and Academic Qualifications
- Bachelor of Medicine, Shanghai Jiao Tong University
- Master of Ophthalmology, Shanghai Jiao Tong University
- Doctor of Philosophy, Sun Yat-sen University
Research Interests
Research Output
- Shi D, Lin Z, Wang W, Tan Z, Shang X, Zhang X, Meng W, Ge Z and He M. A deep learning system for fully automated retinal vessel measurement in high throughput image analysis. Frontiers in Cardiovascular Medicine. 2022;9:823436.
- Lin Z, Shi D, Zhang D, Shang X, He M and Ge Z. Camera adaptation for fundus-image-based CVD risk estimation. International Conference on Medical Image Computing and Computer-Assisted Intervention. 2022:593-603.
- Huang Y, Li C, Shi D, Wang H, Shang X, Wang W, Zhang X, Zhang X, Hu Y and Tang S. Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms. EPMA Journal. 2023;14:73-86.
- He S, Bulloch G, Zhang L, Meng W, Shi D* and He M*. Comparing common retinal vessel caliber measurement software with an automatic deep learning system. Current Eye Research. 2023:1-7.
- Lin Z, Zhang D, Tao Q, Shi D, Haffari G, Wu Q, He M and Ge Z. Medical visual question answering: A survey. Artificial Intelligence in Medicine. 2023:102611.
- He S, Bulloch G, Zhang L, Xie Y, Wu W, He Y, Meng W, Shi D* and He M*. Cross-camera performance of deep learning algorithms to diagnose common ophthalmic diseases: a comparative study highlighting feasibility to portable fundus camera use. Curr Eye Res. 2023;48:857-863.
- Zhu Z, Shi D, Guankai P, Tan Z, Shang X, Hu W, Liao H, Zhang X, Huang Y and Yu H. Retinal age gap as a predictive biomarker for mortality risk. British Journal of Ophthalmology. 2023;107:547-554.
- Fu Y, Yusufu M, Wang Y, He M, Shi D* and Wang R*. Association of retinal microvascular density and complexity with incident coronary heart disease. Atherosclerosis. 2023;380:117196.
- Shi D, He S, Yang J, Zheng Y and He M. One-shot retinal artery and vein segmentation via cross-modality pretraining. Ophthalmology Science. 2023:100363.
- Shi D, Zhang W, He S, Chen Y, Song F, Liu S, Wang R, Zheng Y and He M. Translation of color fundus photography into fluorescein angiography using deep learning for enhanced diabetic retinopathy screening. Ophthalmology Science. 2023:100401.
