mlsanityData to 14 Oct 2026

The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare

arXiv 2411.03287 ↗First posted 5 Nov 2024cs.RO cs.AI cs.ETcited by 2

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Abstract (arXiv)

The potential use of large language models (LLMs) in healthcare robotics can help address the significant demand put on healthcare systems around the world with respect to an aging demographic and a shortage of healthcare professionals. Even though LLMs have already been integrated into medicine to assist both clinicians and patients, the integration of LLMs within healthcare robots has not yet been explored for clinical settings. In this perspective paper, we investigate the groundbreaking developments in robotics and LLMs to uniquely identify the needed system requirements for designing health specific LLM based robots in terms of multi modal communication through human robot interactions (HRIs), semantic reasoning, and task planning. Furthermore, we discuss the ethical issues, open challenges, and potential future research directions for this emerging innovative field.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 104 of its 265 references that are in the map. First posted on arXiv 5 Nov 2024.

Builds on

104 of 265 references.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Benchmarking the Safety of Large Language Models for Robotic Health Attendant Controlcited by 1
  2. 2026PovNet+: A Deep Learning Architecture for Socially Assistive Robots to Learn and Assist with Multiple Activities of Daily Livingcited by 0