72 citations · 108 across the 32 of their papers we have counts for
9 papers · 1 filter
Enhancing Community Vision Screening -- AI Driven Retinal Photography for Early Disease Detection and Patient Trust
Xiaofeng Lei, Yih-Chung Tham, Jocelyn Hui Lin Goh +7
Community vision screening plays a crucial role in identifying individuals with vision loss and preventing avoidable blindness, particularly in rural communities where access to ey…
LEME: Open Large Language Models for Ophthalmology with Advanced Reasoning and Clinical Validation
Hyunjae Kim, Xuguang Ai, Sahana Srinivasan +27
The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinica…
LMOD: A Large Multimodal Ophthalmology Dataset and Benchmark for Large Vision-Language Models
Zhenyue Qin, Yu Yin, Dylan Campbell +6
The prevalence of vision-threatening eye diseases is a significant global burden, with many cases remaining undiagnosed or diagnosed too late for effective treatment. Large vision-…
Block Expanded DINORET: Adapting Natural Domain Foundation Models for Retinal Imaging Without Catastrophic Forgetting
Jay Zoellin, Colin Merk, Mischa Buob +12
Integrating deep learning into medical imaging is poised to greatly advance diagnostic methods but it faces challenges with generalizability. Foundation models, based on self-super…
Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology
Aidan Gilson, Xuguang Ai, Thilaka Arunachalam +19
Despite the potential of Large Language Models (LLMs) in medicine, they may generate responses lacking supporting evidence or based on hallucinated evidence. While Retrieval Augmen…
Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model
Meng Wang, Tian Lin, Aidi Lin +46
Previous foundation models for fundus images were pre-trained with limited disease categories and knowledge base. Here we introduce a knowledge-rich vision-language model (RetiZero…
EyeFound: A Multimodal Generalist Foundation Model for Ophthalmic Imaging
Danli Shi, Weiyi Zhang, Xiaolan Chen +6
Artificial intelligence (AI) is vital in ophthalmology, tackling tasks like diagnosis, classification, and visual question answering (VQA). However, existing AI models in this doma…
A Clinical-oriented Multi-level Contrastive Learning Method for Disease Diagnosis in Low-quality Medical Images
Qingshan Hou, Shuai Cheng, Peng Cao +4
Representation learning offers a conduit to elucidate distinctive features within the latent space and interpret the deep models. However, the randomness of lesion distribution and…
Uncertainty-aware Medical Diagnostic Phrase Identification and Grounding
Ke Zou, Yang Bai, Bo Liu +9
Medical phrase grounding is crucial for identifying relevant regions in medical images based on phrase queries, facilitating accurate image analysis and diagnosis. However, current…