Authors: Sunan He, Yuxiang Nie, Zhixuan Chen, Zhiyuan Cai, Hongmei Wang, Shu Yang, Hao Chen

Published on: April 23, 2024

Impact Score: 8.0

Arxiv code: Arxiv:2404.15127

Summary

• What is new: A diagnosis-guided bootstrapping strategy for constructing vision-language datasets specific to the medical field, leading to the development of the MedDr model.
• Why this is important: The development of large-scale medical vision-language models is limited by the lack of extensive, high-quality image-text data in healthcare.
• What the research proposes: Creating a specialized dataset through a diagnosis-guided bootstrapping strategy and developing MedDr, a versatile foundation model for healthcare.
• Results: The MedDr model shows superior performance in tasks such as visual question answering, medical report generation, and medical image diagnosis.

Technical Details

Technological frameworks used: Diagnosis-guided bootstrapping for dataset construction; retrieval-augmented medical diagnosis strategy for inference

Models used: MedDr, a generalist foundation model

Data used: Diverse medical data modalities, including radiology, pathology, dermatology, retinography, and endoscopy

Potential Impact

Healthcare providers, medical imaging and diagnostic companies, AI-driven healthcare analytics firms

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