mlsanityData to 14 Oct 2026

Clinical Insights: A Comprehensive Review of Language Models in Medicine

arXiv 2408.11735 ↗First posted 21 Aug 2024cs.AIcited by 6

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Abstract (arXiv)

This paper explores the advancements and applications of language models in healthcare, focusing on their clinical use cases. It examines the evolution from early encoder-based systems requiring extensive fine-tuning to state-of-the-art large language and multimodal models capable of integrating text and visual data through in-context learning. The analysis emphasizes locally deployable models, which enhance data privacy and operational autonomy, and their applications in tasks such as text generation, classification, information extraction, and conversational systems. The paper also highlights a structured organization of tasks and a tiered ethical approach, providing a valuable resource for researchers and practitioners, while discussing key challenges related to ethics, evaluation, and implementation.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 131 of its 248 references that are in the map. First posted on arXiv 21 Aug 2024.

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131 of 248 references.

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Citing papers per year: 2024: 2; 2025: 4.

6 papers.