Hasan Alam from the Interactive Machine Learning (IML) Department at DFKI presented our paper, “Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAG”, at the 47th European Conference on Information Retrieval (ECIR 2025), held from April 6–10, 2025 in Lucca, Italy.
ECIR is one of the premier international conferences in the field of information retrieval with a competitive acceptance rate of around 23% in 2025, drawing leading researchers and practitioners from both academia and industry.
The study addresses a key limitation of deep learning in medical imaging: the lack of interpretability that hinders clinical adoption. Focusing on chest X-ray (CXR) imaging, the research introduces a novel framework that combines concept bottleneck models (CBMs) with a multi-agent retrieval-augmented generation (RAG) system for interpretable report generation. Unlike traditional deep learning models, the proposed CBM architecture incorporates a concept bottleneck layer by leveraging a multimodal biomedical vision-language model (VLMs) to learn a concept matrix that explicitly maps visual features to clinically meaningful concepts such as lung opacity, pleural effusion, or consolidation, thereby providing transparency into the decision-making process. These interpretable concept vectors are then used to guide a multi-agent RAG system, in which task-specific reasoning and acting (REACT) agents collaborate to retrieve relevant information and generate coherent, clinically grounded radiology reports. This approach enhances explainability, transparency, and trust, making it more suitable for real-world clinical environments. In addition to traditional evaluation metrics, the study adopts a LLM-as-a-judge methodology, employing five different large language models to assess the generated CXR reports in terms of semantic similarity, accuracy, correctness, clinical usefulness, and consistency.

The presented work at the ECIR 2025

The ECIR 2025 utilized several historic venues in Lucca, notably the San Francesco Church, which served as the primary location for keynotes and main sessions