Transformer Models in Healthcare: A Survey and Thematic Analysis of Potentials, Shortcomings and Risks.

ABSTRACT: Large Language Models (LLMs) such as General Pretrained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT), which use transformer model architectures, have significantly advanced artificial intelligence and natural language processing. Recognized for their ability to capture associative relationships between words based on shared context, these models are poised to transform healthcare by improving diagnostic accuracy, tailoring treatment plans, and predicting patient outcomes. However, there are multiple risks and potentially unintended consequences associated with their use in healthcare applications. This study, conducted with 28 participants using a qualitative approach, explores the benefits, shortcomings, and risks of using transformer models in heal

SUBMITTER: Denecke K 

PROVIDER: S-EPMC10874304 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature