Artificial Neural Networks Analysis for Estimating Bone Mineral Density in an Egyptian Population: Towards Standardization of DXA Measurements
Samir M. Abdel-Mageed,
Amani M. Bayoumi,
Ehab I. Mohamed
Issue:
Volume 1, Issue 3, December 2015
Pages:
52-56
Received:
13 January 2016
Accepted:
17 February 2016
Published:
1 March 2016
DOI:
10.11648/j.ajnna.20150103.11
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Views:
Abstract: An extensive amount of information is currently available to clinical specialists, ranging from detailed demographic characteristics to physical examination and various types of biochemical data. The most important concern in the medical field is to consider the interpretation of data and perform accurate diagnosis. Artificial intelligence method and especially artificial neural network (ANN) algorithms can handle diverse types of medical data and integrate them into categorized outputs. A common bone disease ‘osteoporosis’ does not depend only on bone mineral density (BMD) but also on some other factors e.g., age, weight, height, life-style etc., which play considerable role in the diagnosis of osteoporosis. In this study, we propose a decision making system using demographic variables in an Egyptian population to provide a convenient, accurate and inexpensive solution to predict segmental and total BMD and expect future fracture risk for healthy persons and those with pathologic condition known to be related to BMD. We believe the ANN is a promising tool for estimating and predicting segmental and total BMD values using simple demographic characteristics.
Abstract: An extensive amount of information is currently available to clinical specialists, ranging from detailed demographic characteristics to physical examination and various types of biochemical data. The most important concern in the medical field is to consider the interpretation of data and perform accurate diagnosis. Artificial intelligence method a...
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