TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 38916922

Abstract

OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision management of chronic disease progression.

Authors

  • Zuotian Li
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN 46202, United States.
  • Xiang Liu
    College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China; Anhui Provincial Key Laboratory of Environmental Pollution Control and Resource Reuse, Anhui Jianzhu University, Hefei 230009, China.
  • Ziyang Tang
    Purdue University West Lafayette, Indiana.
  • Nanxin Jin
    Department of Computer and Information Technology, Purdue University, 401 N. Grant St, West Lafayette, IN, USA.
  • Pengyue Zhang
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN 46202, United States.
  • Michael T Eadon
    Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Qianqian Song
    Wake Forest School of Medicine.
  • Yingjie V Chen
    Department of Computer Graphics Technology, Purdue University, West Lafayette, IN 47907, United States.
  • Jing Su
    Indiana University School of Medicine.

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