60 citations · 60 across the 5 of their papers we have counts for
5 papers
Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling
Gregory Holste, Mingquan Lin, Ruiwen Zhou +9
Deep learning has enabled breakthroughs in automated diagnosis from medical imaging, with many successful applications in ophthalmology. However, standard medical image classificat…
Improving Fairness of Automated Chest X-ray Diagnosis by Contrastive Learning
Mingquan Lin, Tianhao Li, Zhaoyi Sun +5
Purpose: Limited studies exploring concrete methods or approaches to tackle and enhance model fairness in the radiology domain. Our proposed AI model utilizes supervised contrastiv…
A scoping review on multimodal deep learning in biomedical images and texts
Zhaoyi Sun, Mingquan Lin, Qingqing Zhu +4
Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the…
An empirical study of using radiology reports and images to improve ICU mortality prediction
Mingquan Lin, Song Wang, Ying Ding +3
Background: The predictive Intensive Care Unit (ICU) scoring system plays an important role in ICU management because it predicts important outcomes, especially mortality. Many sco…
Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations
Mingquan Lin, Yuyun Xiao, Bojian Hou +6
In the United States, primary open-angle glaucoma (POAG) is the leading cause of blindness, especially among African American and Hispanic individuals. Deep learning has been widel…