[2311.12882] LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties

[2311.12882] LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties

arXiv - AI 3 min read

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Abstract page for arXiv paper 2311.12882: LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties

Computer Science > Computation and Language arXiv:2311.12882 (cs) [Submitted on 28 Oct 2023 (v1), last revised 26 Feb 2024 (this version, v3)] Title:LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties Authors:Ummara Mumtaz, Awais Ahmed, Summaya Mumtaz View a PDF of the paper titled LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties, by Ummara Mumtaz and 2 other authors View PDF 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...

Originally published on April 07, 2026. Curated by AI News.

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