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FANS Network Meeting | Data Science | Aarhus |13 September, 2022 | Hybrid Event | Nordic
SAS Employee

Welcome to FANS Network Meeting - focusing on Data Science


Date: 13/09-2022

Time: 13:00-16:00 CET (GMT +1)


  • Denmark: Hybrid (Frederiks Plads 36, 8000 Aarhus C) & Teams (join link will be sent with the registration confirmation email)
  • Finland: Virtual
  • Norway: Virtual
  • Sweden: Virtual
  • Virtual: Microsoft Teams (join link will be sent with the registration confirmation email)

Register: Denmark / Finland / Norway / Sweden




  • Welcome
    • By: Frans Holm, SAS


  • Introduction to the DESERT project at Region Syddanmark, Denmark
    • DESERT - Diagnostic Expert System Enter Real Time
    • Project DESERT trains an artificial intelligence-based decision support system to better detect critical condition in acute patients and rank probabilities for a number of frequent life-threatening conditions based on diagnostic blood and urine tests.
    • Christian will introduce the case and talk about some interesting constrains, such as can we afford to acquire all data in realtime?
    • By: Christian Hardahl, SAS


  • Analytical design in the DESERT project at Region Syddanmark, Denmark
    • Anders will follow up on Christian introduction and dive into the analytics in the solution – looking at the models, tools and code used in the project from a technical angle. 
    • By: Anders Bendix Madsen, SAS


  • Break



  • Using forecast and smoothing techniques together
    • The TSModel procedure in CAS simplifies forecasting from sporadic data. We create an initial forecast, which we smooth and find strange measurements. This is fed to the forecasting routine to create a stable forecast that can be used in several use cases in understanding reservoir and determine the risk for process challenges.
    • By: Anette Østbø Sørensen from CapGemini and Pål Navestad from ConocoPhillips.


  • Analytics and Data Preparation in SAS Enterprise Guide
    • Executing linear regressi cvon analysis with SAS Enterprise Guide together with some data preparation activities.
    • Data pre-processing includes missing value imputation, outlier filtering and variables transformations.
    • By Jussi Varjus, SAS



  • TBD



  • Closing
    • By Frans Holm, SAS


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You will find the presentations here below: