The success of foundation models such as ChatGPT and AlphaFold has spurred significant
interest in building similar models for electronic medical records (EMRs) to improve patient …

Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …

The utilization of large language models (LLMs) in the Healthcare domain has generated
both excitement and concern due to their ability to effectively respond to freetext queries with …

Objective Clinical knowledge-enriched transformer models (eg, ClinicalBERT) have state-of-
the-art results on clinical natural language processing (NLP) tasks. One of the core …

Large Language Models (LLMs) recently demonstrated extraordinary capability in various
natural language processing (NLP) tasks including language translation, text generation …

Transformer-based pretrained language models (PLMs) have started a new era in modern
natural language processing (NLP). These models combine the power of transformers …

Single-task models have proven pivotal in solving specific tasks; however, they have
limitations in real-world applications where multi-tasking is necessary and domain shifts are …

Abstract International Classification of Diseases (ICD) coding plays an important role in
systematically classifying morbidity and mortality data. In this study, we propose a …

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

Deep neural language models have set new breakthroughs in many tasks of Natural
Language Processing (NLP). Recent work has shown that deep transformer language …