ChatGPT, GPT-4, and Other Large Language Models: The Next Revolution for Clinical Microbiology?

ChatGPT, GPT-4, and Bard are highly advanced natural language process–based computer programs (chatbots) that simulate and process human conversation in written or spoken form. Recently released by the company OpenAI, ChatGPT was trained on billions of unknown text elements (tokens) and rapidly gain...

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Publicado en:Clinical Infectious Diseases Vol. 77; no. 9; pp. 1322 - 1329
Autor principal: Egli, Adrian
Formato: pictorial questions and answers tables/charts Journal Article
Publicado: Oxford University Press / USA Nov2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: ChatGPT, GPT-4, and Other Large Language Models: The Next Revolution for Clinical Microbiology?
      aug:
        au: Egli, Adrian
        affil: Institute of Medical Microbiology, University of Zurich , Zurich , Switzerland
      sug:
        subj:
          Artificial Intelligence
          Natural Language Processing
          Communicable Diseases Microbiology
          Technology, Medical
          Diagnosis, Laboratory
      ab: ChatGPT, GPT-4, and Bard are highly advanced natural language process–based computer programs (chatbots) that simulate and process human conversation in written or spoken form. Recently released by the company OpenAI, ChatGPT was trained on billions of unknown text elements (tokens) and rapidly gained wide attention for its ability to respond to questions in an articulate manner across a wide range of knowledge domains. These potentially disruptive large language model (LLM) technologies have a broad range of conceivable applications in medicine and medical microbiology. In this opinion article, I describe how chatbot technologies work and discuss the strengths and weaknesses of ChatGPT, GPT-4, and other LLMs for applications in the routine diagnostic laboratory, focusing on various use cases for the pre- to post-analytical process.
      pubtype: Academic Journal
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        questions and answers
        tables/charts
        Journal Article
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    language: English
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