Large language models (LLMs) have recently demonstrated their potential in clinical
applications, providing valuable medical knowledge and advice. For example, a large dialog …

Radiology report generation (RRG) aims to automatically generate free-text descriptions
from clinical radiographs, eg, chest X-Ray images. RRG plays an essential role in promoting …

Radiology report generation aims to automatically generate a clinically accurate and
coherent paragraph from the X-ray image, which could relieve radiologists from the heavy …

Deep neural networks have been integrated into the whole clinical decision procedure
which can improve the efficiency of diagnosis and alleviate the heavy workload of …

Increasing demands on medical imaging departments are taking a toll on the radiologist's
ability to deliver timely and accurate reports. Recent technological advances in artificial …

Medical imaging plays a crucial role in diagnosis, with radiology reports serving as vital
documentation. Automating report generation has emerged as a critical need to alleviate the …

The goal of automatic report generation is to generate a clinically accurate and coherent
phrase from a single given X-ray image, which could alleviate the workload of traditional …

The scaling laws and extraordinary performance of large foundation models motivate the
development and utilization of such models in biomedicine. However, despite early …

Fine-grained vision-language models (VLM) have been widely used for inter-modality local
alignment between the predefined fixed patches and textual words. However, in medical …

Although deep cross-modal hashing methods have shown superiorities for cross-modal
retrieval recently, there is a concern about potential data privacy leakage when training the …