Resources

The development of robust echocardiography analyses has been limited by the scarcity of well-annotated, labeled echocardiogram datasets. We introduce the Structured Viewing Classification Annotations From the MIMIC-IV-ECHO Dataset (ECHOVIEW), a deri…

Large Vision Language Models (LVLMs) have recently achieved superior performance in various tasks on natural image and text data, which inspires a large amount of studies for LVLMs fine-tuning and training. Despite their advancements, there has been…

The respiratory microbiome plays a critical role in metabolism, immune system maturation, and protection against pathogens. Traditionally, respiratory microbiology in pneumonia focused on identifying a specific pathogen, often disregarding normal or…

Recent progress in Large Vision-Language Models (LVLMs) has enabled promising applications in medical tasks such as report generation and visual question answering. However, existing benchmarks focus mainly on the final diagnostic answer, offering l…

Doctor-patient consultations require multi-turn, context-aware communication tailored to diverse patient personas. Training or evaluating doctor LLMs in such settings requires realistic patient interaction systems. However, existing simulators often…

Large language models (LLMs) have shown impressive capabilities in solving a wide range of tasks based on human instructions. However, developing a conversational AI assistant for electronic health record (EHR) data remains challenging due to the la…

This dataset, Swiss-Mammo, contains 28 manually constructed German mammography reports, each paired with an English translation. The reports are stratified across BI-RADS categories 0 through 6, with four reports per category. All reports were manua…

Brain–computer interfaces (BCIs) have wide-ranging applications as solutions for replacing or substituting neural output that has been lost because of severe neuromuscular injury or disease, such as individuals with late-stage amyotrophic lateral sc…

With the rapid development of generative LLMs (large language models) in the field of natural language processing, their potential in medical applications has become increasingly evident. However, most existing studies rely on exam-style questions o…

Large-language models (LLMs) show promise for extracting information from clinical notes. Deploying these models at scale can be challenging due to high computational costs, regulatory constraints, and privacy concerns. To address these challenges, …