Back to search

Article

MRG-R3: Retrieval-Reflection-Reward via Multimodal LLMs Advances Clinical Automated Medical Report Generation

2025-11-20

Abstract excerpt

<title>Abstract</title> <p> Automated medical report generation (MRG) holds promise for tackling mounting radiologist workloads and enhancing diagnostic efficiency. Current approaches, however, are limited by deficiencies in contextual reasoning and clinical integration. Here we introduce MRG-R <sup>3</sup> , a novel Retrieval-Reflection-Reward framework, which enhances MRG by emulating three key behaviors thr...

Topics

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

Identifiers and source

Literature Corpus work
e901e131-b31f-5845-bbbd-7fb66c9bcbde
DOI
10.21203/rs.3.rs-7914595/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
MRG-R3: Retrieval-Reflection-Reward via Multimodal LLMs Advances Clinical Automated Medical Report GenerationDOI 10.21203/rs.3.rs-7914595/v1
Select a neighboring publication to make it the new centre.