The paucity of high-quality medical imaging datasets could be mitigated by machine
learning models that generate compositionally diverse images that faithfully represent …

Large language models (LLMs) have rapidly become important tools in Biomedical and
Health Informatics (BHI), potentially enabling new ways to analyze data, treat patients, and …

The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a
wave of opportunities in computational healthcare. The interactive nature of these models …

With the significant advancements of Large Language Models (LLMs) in the field of Natural
Language Processing (NLP), the development of image-text multimodal models has …

With the significant advancements of Large Language Models (LLMs) in the field of Natural
Language Processing (NLP), the development of image-text multimodal models has …

Biomedical imaging datasets are often small and biased, meaning that real-world
performance of predictive models can be substantially lower than expected from internal …

We present Pix2Gif, a motion-guided diffusion model for image-to-GIF (video) generation.
We tackle this problem differently by formulating the task as an image translation problem …

The limited availability of 3D medical image datasets, due to privacy concerns and high
collection or annotation costs, poses significant challenges in the field of medical imaging …

Chest X-ray imaging (CXR) is an important diagnostic tool used in hospitals to assess
patient conditions and monitor changes over time. Generative models, specifically diffusion …

Integrating multi-modal clinical data, such as electronic health records (EHR) and chest X-
ray images (CXR), is particularly beneficial for clinical prediction tasks. However, in a …