Arterial Blood Gases Forecast Optimization by Artificial Neural Network Method

  • Wiesław Wajs
  • Piotr Wais
  • Marcin Ochab
  • Hubert WojtowiczEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 471)


Arterial blood gas sampling represents the gold standard method for acquiring patients’ acid-base status. It is proposed that blood gas values could be measured using arterialized earlobe blood samples. Pulse oximetry plus transcutaneous carbon dioxide measurement is an alternative method of obtaining similar information as well. Since dynamics of biochemical changes occurring in the blood is an individual feature which changes during the healing process authors proposed forecast models developed using artificial neural networks. The networks are trained with data vectors containing short term (72 h) history windows of four blood gasometry parameters. Several different optimization algorithms are used in the training phase to create a set of models from which the best prediction model is then selected.


Arterial blood gas Forecast Artificial neural networks 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Wiesław Wajs
    • 1
  • Piotr Wais
    • 2
  • Marcin Ochab
    • 3
  • Hubert Wojtowicz
    • 1
    Email author
  1. 1.The University of RzeszówRzeszówPoland
  2. 2.State Higher Vocational School in KrosnoKrosnoPoland
  3. 3.AGH University of Science and TechnologyKrakówPoland

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