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Leveraging data science for a personalized haemodialysis

Author
Hueso, M.; Haro, L.; Calabria, J.; Dal-Re, R.; Tebe, C.; Gibert, Karina; Cruzado, J. M.; Vellido, A.
Type of activity
Journal article
Journal
Kidney diseases
Date of publication
2020-11
Volume
6
Number
6
First page
385
Last page
394
DOI
10.1159/000507291
Repository
http://hdl.handle.net/2117/340805 Open in new window
URL
https://www.karger.com/Article/FullText/507291 Open in new window
Abstract
The 2019 Science for Dialysis Meeting at Bellvitge University Hospital was devoted to the challenges and opportunities posed by the use of data science to facilitate precision and personalized medicine in nephrology, and to describe new approaches and technologies. The meeting included separate sections for issues in data collection and data analysis. As part of data collection, we presented the institutional ARGOS e-health project, which provides a common model for the standardization of clinic...
Citation
Hueso, M. [et al.]. Leveraging data science for a personalized haemodialysis. "Kidney diseases", Novembre 2020, vol. 6, núm. 6, p. 385-394.
Keywords
Artificial intelligence, Data science, Haemodialysis, Machine learning, Personalized medicine, Pragmatic clinical trials
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group
SOCO - Soft Computing

Participants

  • Hueso, Miguel  (author)
  • Haro Martín, Luis de  (author)
  • Calabria, Jordi  (author)
  • Dal-Re, R  (author)
  • Tebe, C  (author)
  • Gibert, Karina  (author)
  • Cruzado, Josep M  (author)
  • Vellido Alcacena, Alfredo  (author)

Attachments