Article

Specialized curricula for training vision-language models in retinal image analysis

2024-11-19

Abstract excerpt

<title>Abstract</title> <p>Clinicians spend a significant amount of time reviewing medical images and transcribing their findings regarding patient diagnosis, referral and treatment in text form. Vision-language models (VLMs), which automatically interpret images and summarize their findings as text, have enormous potential to alleviate clinical workloads and increase patient access to high-quality medical care....

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: cc071dd1-9f72-51da-842b-1ad3d6e7f08d
DOI: 10.21203/rs.3.rs-4720415/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Specialized curricula for training vision-language models in retinal image analysisDOI 10.21203/rs.3.rs-4720415/v1Read

FFA-GPT: an Interactive Visual Question Answering System for Fundus Fluorescein AngiographySemantic proximity Read

How Far Have Large Language Models Advanced in Ophthalmology? A Systematic Review of Their Development, Evaluation, and Readiness for Clinical UseSemantic proximity Read

Compact Vision–Language Models Enable Efficient and Interpretable Automated OCT Analysis Through Layer Specific Multimodal LearningSemantic proximity Read

How Far Have Large Language Models Advanced in Ophthalmology? A Systematic Review of Their Development, Evaluation, and Readiness for Clinical UseSemantic proximity Read

Multimodal Large Language Models are Generalist Medical Image InterpretersSemantic proximity Read

Open-source DeepSeek-R1 Outperforms Proprietary Non-Reasoning Large Language Models With and Without Retrieval-Augmented GenerationSemantic proximity Read

AI Performance on Image-based Medical Case Scenarios: A Cross-Sectional Comparative StudySemantic proximity Read

Enhancing Patient Education With AI:A Readability Analysis of AI-Generated Versus American Academy of Ophthalmology Online Patient Education MaterialsSemantic proximity Read

GlaucoRAG: A Retrieval-Augmented Large Language Model for Expert-Level Glaucoma AssessmentSemantic proximity Read

Learning Ophthalmologist Clinical Reasoning for Glaucoma Diagnosis from Fundus ImagesSemantic proximity Read

Board-Level Performance of Leading Open-Weight Vision-Language Models on the Japanese Diagnostic Radiology Board Examination: Reasoning, Image-Input, and Language EffectsSemantic proximity Read

UWF-FM: A Foundation Model for Comprehensive Ultra-Widefield Retinal AssessmentSemantic proximity Read