AI Article Synopsis

  • The study reviewed the use of large language models (LLMs) in medicine, analyzing 550 studies and highlighting their impact on diagnostics, medical writing, education, and project management.
  • LLMs improved tasks like drafting medical documents and enhancing communication between doctors and patients, but challenges such as limited contextual understanding and the danger of over-reliance were noted.
  • Future research should address multimodal LLMs, deeper algorithm insights, and ensuring their responsible integration into healthcare practices.

Article Abstract

This study systematically reviewed the application of large language models (LLMs) in medicine, analyzing 550 selected studies from a vast literature search. LLMs like ChatGPT transformed healthcare by enhancing diagnostics, medical writing, education, and project management. They assisted in drafting medical documents, creating training simulations, and streamlining research processes. Despite their growing utility in assisted diagnosis and improving doctor-patient communication, challenges persisted, including limitations in contextual understanding and the risk of over-reliance. The surge in LLM-related research indicated a focus on medical writing, diagnostics, and patient communication, but highlighted the need for careful integration, considering validation, ethical concerns, and the balance with traditional medical practice. Future research directions suggested a focus on multimodal LLMs, deeper algorithmic understanding, and ensuring responsible, effective use in healthcare.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11091685PMC
http://dx.doi.org/10.1016/j.isci.2024.109713DOI Listing

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