Surviving ChatGPT in healthcare.

Journal: Frontiers in radiology
Published Date: Feb 23, 2024

Abstract

At the dawn of of Artificial General Intelligence (AGI), the emergence of large language models such as ChatGPT show promise in revolutionizing healthcare by improving patient care, expanding medical access, and optimizing clinical processes. However, their integration into healthcare systems requires careful consideration of potential risks, such as inaccurate medical advice, patient privacy violations, the creation of falsified documents or images, overreliance on AGI in medical education, and the perpetuation of biases. It is crucial to implement proper oversight and regulation to address these risks, ensuring the safe and effective incorporation of AGI technologies into healthcare systems. By acknowledging and mitigating these challenges, AGI can be harnessed to enhance patient care, medical knowledge, and healthcare processes, ultimately benefiting society as a whole.

Authors

  • Zhengliang Liu
    School of Computing, University of Georgia, Athens, GA, United States.
  • Lu Zhang
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Zihao Wu
    School of Computing, University of Georgia, Athens, GA, United States.
  • Xiaowei Yu
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Chao Cao
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Haixing Dai
    School of Computing, University of Georgia, Athens, GA, United States.
  • Ninghao Liu
    School of Computing, University of Georgia, Athens, GA, United States.
  • Jun Liu
    Department of Radiology, Second Xiangya Hospital, Changsha, Hunan, China.
  • Wei Liu
    Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • Quanzheng Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Dinggang Shen
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Dajiang Zhu
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Tianming Liu
    School of Computing, University of Georgia, Athens, GA, United States.

Keywords

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