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Surviving ChatGPT in healthcare.
Liu, Zhengliang; Zhang, Lu; Wu, Zihao; Yu, Xiaowei; Cao, Chao; Dai, Haixing; Liu, Ninghao; Liu, Jun; Liu, Wei; Li, Quanzheng; Shen, Dinggang; Li, Xiang; Zhu, Dajiang; Liu, Tianming.
Affiliation
  • Liu Z; School of Computing, University of Georgia, Athens, GA, United States.
  • Zhang L; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Wu Z; School of Computing, University of Georgia, Athens, GA, United States.
  • Yu X; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Cao C; Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Dai H; School of Computing, University of Georgia, Athens, GA, United States.
  • Liu N; School of Computing, University of Georgia, Athens, GA, United States.
  • Liu J; Department of Radiology, Second Xiangya Hospital, Changsha, Hunan, China.
  • Liu W; Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • Li Q; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Shen D; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
  • Li X; Department of Research and Development, Shanhai United Imaging Intelligence Co., Ltd., Shanghai, China.
  • Zhu D; Shanghai Clinical Research and Trial Center, Shanghai, China.
  • Liu T; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Front Radiol ; 3: 1224682, 2023.
Article in En | MEDLINE | ID: mdl-38464946
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Radiol Year: 2023 Document type: Article Affiliation country: United States Country of publication: Switzerland
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Radiol Year: 2023 Document type: Article Affiliation country: United States Country of publication: Switzerland