Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis

Introduction

Large language models (LLMs) are reshaping biomedical research and healthcare by improving clinical decision-making, patient communication, and medical document analysis. This article reviews their applications, benefits, and challenges.

Applications of LLMs in Healthcare

Clinical Decision Support

LLMs assist physicians by analyzing vast medical datasets to provide evidence-based recommendations, reducing diagnostic errors and enhancing treatment plans.

Patient Interaction and Communication

AI-driven chatbots and virtual assistants improve patient engagement by answering health-related questions, scheduling appointments, and offering mental health support.

Medical Document Analysis

LLMs streamline administrative tasks by summarizing patient records, extracting relevant clinical data, and automating documentation processes.

Ethical and Practical Challenges

While LLMs offer numerous benefits, concerns regarding data privacy, biases in AI models, and regulatory challenges must be addressed to ensure their safe and equitable deployment.

Conclusion

The integration of LLMs in healthcare holds great promise for efficiency and improved patient outcomes. Further research and ethical considerations will shape their responsible use in medical settings.