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
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