Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias.

Journal: PeerJ
PMID: 39512310

Abstract

BACKGROUND: Plasma cell dyscrasias encompass a diverse set of disorders, where early and precise diagnosis is essential for optimizing patient outcomes. Despite advancements, current diagnostic methodologies remain underutilized in applying artificial intelligence (AI) to routine laboratory data. This study seeks to construct an AI-driven model leveraging standard laboratory parameters to enhance diagnostic accuracy and classification efficiency in plasma cell dyscrasias.

Authors

  • Bihua Yao
    Laboratory Medicine Center, Department of Clinical Laboratory, The First People's Hospital of Jiashan affiliated to Jiaxing University, Jiashan, Zhejiang, China.
  • Yicheng Liu
    Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China.
  • Yuwei Wu
  • Siyu Mao
    Laboratory Medicine Center, Department of Clinical Laboratory, The First People's Hospital of Jiashan affiliated to Jiaxing University, Jiashan, Zhejiang, China.
  • Hangbiao Zhang
    Shanghai Jiaotong University, Shanghai, China.
  • Lei Jiang
    Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai 200433, China.
  • Cheng Fei
  • Shuang Wang
    Engineering Technology Research Center of Shanxi Province for Opto-Electric Information and Instrument, Taiyuan 030051, China. S1507038@st.nuc.edu.cn.
  • Jijun Tong
    Zhejiang Sci-Tech University, Hangzhou, China.
  • Jianguo Wu
    School of Life Sciences, Arizona State University, Tempe, AZ, 85281, USA; School of Sustainability, Julie A. Wrigley Global Institute of Sustainability, Arizona State University, Tempe, AZ, 85281, USA; Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China.

Keywords

External Resources

Popular Topics
Recent Journals