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The Role of Language Models in Modern Healthcare: A Comprehensive Review

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arxiv 2409.16860 v1 pith:GBWTR6U5 submitted 2024-09-25 cs.CV cs.AIcs.CL

The Role of Language Models in Modern Healthcare: A Comprehensive Review

classification cs.CV cs.AIcs.CL
keywords healthcarelanguagemodelsllmsmedicaldataethicalreview
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The application of large language models (LLMs) in healthcare has gained significant attention due to their ability to process complex medical data and provide insights for clinical decision-making. These models have demonstrated substantial capabilities in understanding and generating natural language, which is crucial for medical documentation, diagnostics, and patient interaction. This review examines the trajectory of language models from their early stages to the current state-of-the-art LLMs, highlighting their strengths in healthcare applications and discussing challenges such as data privacy, bias, and ethical considerations. The potential of LLMs to enhance healthcare delivery is explored, alongside the necessary steps to ensure their ethical and effective integration into medical practice.

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Cited by 1 Pith paper

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  1. UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA

    cs.CV 2026-06 unverdicted novelty 4.0

    UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.