output
20182026
most citedLarge AI Models in Health Informatics: Applications, Challenges, and the Future

238 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2026

Full end-to-end diagnostic workflow automation of 3D OCT via foundation model-driven AI for retinal diseases

Jinze Zhang, Jian Zhong, Li Lin +18

Optical coherence tomography (OCT) has revolutionized retinal disease diagnosis with its high-resolution and three-dimensional imaging nature, yet its full diagnostic automation in…

cs.CV2025★ 1 cited

DiffCamera: Arbitrary Refocusing on Images

Yiyang Wang, Xi Chen, Xiaogang Xu +2

The depth-of-field (DoF) effect, which introduces aesthetically pleasing blur, enhances photographic quality but is fixed and difficult to modify once the image has been created. T…

cs.CV2020★ 2 cited

Difficulty-aware Glaucoma Classification with Multi-Rater Consensus Modeling

Shuang Yu, Hong-Yu Zhou, Kai Ma +4

Medical images are generally labeled by multiple experts before the final ground-truth labels are determined. Consensus or disagreement among experts regarding individual images re…

cs.CV2020★ 2 cited

Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning

Junde Wu, Shuang Yu, Wenting Chen +5

Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts. However, a well trained deep learning model deman…

cs.CV2019★ 3 cited

Learn to Segment Retinal Lesions and Beyond

Qijie Wei, Xirong Li, Weihong Yu +8

Towards automated retinal screening, this paper makes an endeavor to simultaneously achieve pixel-level retinal lesion segmentation and image-level disease classification. Such a m…

cs.CV2018★ 8 cited

Performance assessment of the deep learning technologies in grading glaucoma severity

Yi Zhen, Lei Wang, Han Liu +2

Objective: To validate and compare the performance of eight available deep learning architectures in grading the severity of glaucoma based on color fundus images. Materials and Me…