Large language models (LLMs), such as ChatGPT, have received substantial attention due
to their capabilities for understanding and generating human language. While there has …

Electronic Health Records (EHRs) play an important role in the healthcare system. However,
their complexity and vast volume pose significant challenges to data interpretation and …

Large Language Models (LLMs) have demonstrated impressive performance on Natural
Language Processing (NLP) tasks, such as Question Answering, Summarization, 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 …

Specifically focusing on the landscape of abstractive text summarization, as opposed to
extractive techniques, this survey presents a comprehensive overview, delving into state-of …

Chest X-rays (CXRs) are the most frequently performed imaging test in clinical practice.
Recent advances in the development of vision-language foundation models (FMs) give rise …

The use of machine learning (ML) to detect depression in online settings has emerged as an
important health and wellness use case. In particular, the use of deep learning methods for …

LLMs are revolutionizing NLP tasks. However, the use of the most advanced LLMs, such as
GPT-4, is often prohibitively expensive for most specialized fields. We introduce HEAL, the …

Medical text generation aims to assist with administrative work and highlight salient
information to support decision-making. To reflect the specific requirements of medical text …

Retrieval-augmented generation (RAG) is a powerful technique to facilitate language model
with proprietary and private data, where data privacy is a pivotal concern. Whereas …