Artificial neural networks to predict future bone mineral density and bone loss rate in Japanese postmenopausal women.

ABSTRACT:

Objective

Predictions of the future bone mineral density and bone loss rate are important to tailor medicine for women with osteoporosis, because of the possible presence of personal risk factors affecting the severity of osteoporosis in the future. We investigated whether it was possible to predict bone mineral density and bone loss rate in the future using artificial neural networks.

Results

A total of 135 women over 50 years old residing in T town of Wakayama Prefecture, Japan were analyzed to establish a statistical model. Artificial neural networks models were constructed using the two variables of bone mineral density and bone loss rate. The multiple correlation coefficients between the actual and measured values for lumbar and femoral bone mineral densities in 2003 showed R² = 0.929 and R² = 0.880, respectively, by linear regression analyses, while the values for bone loss rates in lumbar and femoral bone mineral densities were R² = 0.694 and R² = 0.609, respectively. Statistical models by artificial neural networks were superior to those by multiple regression analyses. The prediction of future bone mineral density values estimated by artificial neural networks was considered to be useful as a tool to tailor medicine for the early diagnosis of and intervention for women osteoporosis with women.

SUBMITTER: Shioji M 

PROVIDER: S-EPMC5681768 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature