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20222026
most citedLarge AI Models in Health Informatics: Applications, Challenges, and the Future

238 citations · 458 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

EventVGGT: Exploring Cross-Modal Distillation for Consistent Event-based Depth Estimation

Yinrui Ren, Jinjing Zhu, Kanghao Chen +8

Event cameras offer superior sensitivity to high-speed motion and extreme lighting, making event-based monocular depth estimation a promising approach for robust 3D perception in c…

cs.CV2025

Native Intelligence Emerges from Large-Scale Clinical Practice: A Retinal Foundation Model with Deployment Efficiency

Jia Guo, Jiawei Du, Shengzhu Yang +21

Current retinal foundation models remain constrained by curated research datasets that lack authentic clinical context, and require extensive task-specific optimization for each ap…

cs.CV2024★ 2 cited

VisionCLIP: An Med-AIGC based Ethical Language-Image Foundation Model for Generalizable Retina Image Analysis

Hao Wei, Bowen Liu, Minqing Zhang +2

Generalist foundation model has ushered in newfound capabilities in medical domain. However, the contradiction between the growing demand for high-quality annotated data with patie…

cs.CV2023

CauDR: A Causality-inspired Domain Generalization Framework for Fundus-based Diabetic Retinopathy Grading

Hao Wei, Peilun Shi, Juzheng Miao +5

Diabetic retinopathy (DR) is the most common diabetic complication, which usually leads to retinal damage, vision loss, and even blindness. A computer-aided DR grading system has a…

cs.CV2023★ 142 cited

Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation

Peilun Shi, Jianing Qiu, Sai Mu Dalike Abaxi +3

In this paper, we examine the recent Segment Anything Model (SAM) on medical images, and report both quantitative and qualitative zero-shot segmentation results on nine medical ima…

cs.CV2023★ 1 cited

EVEN: An Event-Based Framework for Monocular Depth Estimation at Adverse Night Conditions

Peilun Shi, Jiachuan Peng, Jianing Qiu +3

Accurate depth estimation under adverse night conditions has practical impact and applications, such as on autonomous driving and rescue robots. In this work, we studied monocular…

cs.CV2022

Clustering Egocentric Images in Passive Dietary Monitoring with Self-Supervised Learning

Jiachuan Peng, Peilun Shi, Jianing Qiu +12

In our recent dietary assessment field studies on passive dietary monitoring in Ghana, we have collected over 250k in-the-wild images. The dataset is an ongoing effort to facilitat…