LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties

TL;DR

This paper reviews the recent use of Large Language Models in healthcare, focusing on their applications in diagnostics and treatment across multiple medical specialties, and discusses associated challenges and opportunities.

Contribution

It provides a comprehensive overview of LLM applications in healthcare, highlighting their innovative roles and addressing integration challenges across medical domains.

Findings

LLMs support diagnostics in cancer, dermatology, dental, neurodegenerative, and mental health care.

They offer transformative contributions to medical diagnostics and patient care.

The paper discusses challenges and opportunities in integrating LLMs into healthcare.

Abstract

We aim to present a comprehensive overview of the latest advancements in utilizing Large Language Models (LLMs) within the healthcare sector, emphasizing their transformative impact across various medical domains. LLMs have become pivotal in supporting healthcare, including physicians, healthcare providers, and patients. Our review provides insight into the applications of Large Language Models (LLMs) in healthcare, specifically focusing on diagnostic and treatment-related functionalities. We shed light on how LLMs are applied in cancer care, dermatology, dental care, neurodegenerative disorders, and mental health, highlighting their innovative contributions to medical diagnostics and patient care. Throughout our analysis, we explore the challenges and opportunities associated with integrating LLMs in healthcare, recognizing their potential across various medical specialties despite existing limitations. Additionally, we offer an overview of handling diverse data types within the medical field.