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Mining clinical pathways for daily insulin therapy of diabetic children

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Publication:2042993
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DOI10.34768/amcs-2021-0008zbMath1469.92059OpenAlexW3205986371MaRDI QIDQ2042993

Wojciech Froelich, Grazyna Deja, Rafał Deja

Publication date: 22 July 2021

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://rebus.us.edu.pl/bitstream/20.500.12128/20039/1/Froelich_Deja_Mining_clinical_pathways.pdf

zbMATH Keywords

decision support systemsdiabetes mellitusmodeling clinical pathways


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Medical applications (general) (92C50)




Cites Work

  • Unnamed Item
  • Machine learning techniques combined with dose profiles indicate radiation response biomarkers
  • Fusion of clinical data: a case study to predict the type of treatment of bone fractures
  • Mathematical modeling of the glucose-insulin system: a review
  • Bayesian Reasoning and Machine Learning
  • A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
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