Harnessing GPT-4 for automated error detection in pathology reports: Implications for oncology diagnostics.

Journal: Digital health
Published Date:

Abstract

OBJECTIVE: Accurate pathology reports are crucial for the diagnosis and treatment planning of cancer patients. However, these reports are prone to errors due to time pressures, subjective interpretation, and inconsistencies among professionals. Addressing these errors is vital for improving oncology care outcomes. Artificial intelligence (AI) systems, such as GPT-4, offer the potential to enhance diagnostic accuracy and efficiency.

Authors

  • Xiongwen Yang
    Department of Thoracic Surgery, Guizhou Provincial People's Hospital, No. 83, Zhongshan East Road, Guiyang, , Guizhou, China. yangxiongwen@gz5055.com.
  • Yun Zhang
    Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
  • Jinyan Jiang
    Department of Pathology, The First People's Hospital of Chenzhou, Chenzhou, Hunan, China.
  • Zhijun Chen
    Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430070, China.
  • Rinasu Bai
    Department of Pathology, Beijing Fengtai Hospital, Beijing, China.
  • Zihao Yuan
    The Second Clinical Medical College, Guangdong Medical University, Dongguan, Guangdong, China.
  • Longyan Dong
    The Second Clinical Medical College, Guangdong Medical University, Dongguan, Guangdong, China.
  • Yi Xiao
    Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China.
  • Di Liu
    Laboratory of Nutrition and Functional Food, College of Food Science and Engineering, Jilin University, Changchun, China.
  • Huiyin Deng
    Department of Anesthesiology, the Third Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Jian Huang
    Center for Informational Biology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, P. R. China.
  • Huiyou Shi
    Department of Thoracic Surgery, Guizhou Provincial People's Hospital, Guiyang, China.
  • Dan Liu
    Department of Bioengineering, Temple University, Philadelphia, PA, United States.
  • Maoli Liang
    NHC Key Laboratory of Pulmonary Immunological Diseases, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
  • Weijuan Tang
    Department of Thoracic Surgery, Guizhou Provincial People's Hospital, Guiyang, China.
  • Chuan Xu
    Department of Thoracic Surgery, Guizhou Provincial People's Hospital, No. 83, Zhongshan East Road, Guiyang, , Guizhou, China. xuchuan89757@163.com.

Keywords

No keywords available for this article.