CLINICAL APPLICATION OF A STATISTICAL LEARNING APPROCH FOR PREDICTING DRY WEIGHT IN HEMODIALYSIS USING BIG DATA ANALYTICS

 

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E-Poster Presentation

During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center. 

Preparing your E-Poster

Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.

​E-Poster Submission Deadline

Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.​

E-Poster Format Requirements
  • PDF file
  • Layout: Portrait (vertical orientation)
  • One page only (Dim A4: 210 x 297mm or PPT)
  • E-Poster can be prepared in PowerPoint (one (1) PowerPoint slide) but must be saved and submitted as PDF file.
  • File Size: Maximum file size is 2 Megabytes (2 MB)
  • No hyperlinks, animated images, animations, and slide transitions
  • Language: English
  • Include your abstract number
  • E-posters can include QR codes, tables and photos
 
CLINICAL APPLICATION OF A STATISTICAL LEARNING APPROCH FOR PREDICTING DRY WEIGHT IN HEMODIALYSIS USING BIG DATA ANALYTICS

Please follow the instructions below to input your abstract title.

Abstract titles should be brief and reflect the content of the abstract.

  • The title will not be accepted if it exceeds 25 words.
  • Type in CAPITAL LETTERS.
  • Lowercase may be used for abbreviations only, for example, mRNA.
Ping
Cheng
Ping Cheng cheercheng0208@163.com Huashan Hospital affiliated to Fudan University Department of Nephrology Shanghai China *
Yi Wang wangyi_fudan@fudan.edu.cn Fudan University College of Life Sciences Shanghai China -
Mengjing Wang fiyona27@126.com Huashan Hospital affiliated to Fudan University Department of Nephrology Shanghai China -
Jing Qian money_0921@163.com Huashan Hospital affiliated to Fudan University Department of Nephrology Shanghai China -
Jing Chen chenjing1998@fudan.edu.cn Huashan Hospital affiliated to Fudan University Department of Nephrology Shanghai China -
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