• DocumentCode
    2343017
  • Title

    Predicting Parathyroid Hormone Levels in Diabetic Hemodialysis Patients Using Neural Networks

  • Author

    Bumanlag, Jesse ; Zarei, Anahita ; Ghazi, Pourya ; Kapre, Sheela ; Frank, Lawrence

  • Author_Institution
    Sch. of Eng. & Comput. Sci., Univ. of the Pacific, Stockton, CA, USA
  • fYear
    2009
  • fDate
    2-4 April 2009
  • Firstpage
    221
  • Lastpage
    224
  • Abstract
    Parathyroid Hormone (PTH) is an important biochemical indicator for the medical condition of osteodystrophy in patients on hemodialysis. Prior studies have been conducted to classify hemodialysis patients based on their PTH level, using neural networks. This paper introduces the possibilities of predicting parathyroid hormone levels in the more specific case of diabetic patients. The performance of two different neural network models, a general case and a diabetic case, were examined and compared. Results of this comparison showed improved prediction for PTH levels in patients with diabetes.
  • Keywords
    biochemistry; diseases; medical diagnostic computing; neural nets; biochemical indicator; diabetic hemodialysis patients; neural networks; osteodystrophy; parathyroid hormone levels; Artificial neural networks; Biochemistry; Blood; Bones; Calcium; Computer networks; Diabetes; Medical diagnostic imaging; Neural networks; Sugar; A1C; Artificial Intelligence; Diabetes; Medicine; Neural Network; Parathyroid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Engineering and Information, 2009. ICC '09. International Conference on
  • Conference_Location
    Fullerton, CA
  • Print_ISBN
    978-0-7695-3538-8
  • Type

    conf

  • DOI
    10.1109/ICC.2009.55
  • Filename
    5328134