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Computational models for detection of endocrinopathy in subfertile males
- Source :
- International Journal of Impotence Research. 20:79-84
- Publication Year :
- 2007
- Publisher :
- Springer Science and Business Media LLC, 2007.
-
Abstract
- The observation that men with sperm density greater than 10 million/ml had low probability of endocrinopathy led to a refinement in the evaluation of subfertility. Using statistical methods, we sought to provide a more accurate prediction of which patients have an endocrinopathy, and to report the outcome as the odds of having disease. In addition, by examining the parameters that influenced the model significantly, the underlying pathophysiology might be better understood. Records of 1035 men containing variables including testis volume, sperm density, motility as well as the presence of endocrinopathy were randomized into 'training' and 'test' data sets. We modeled the data set using linear and quadratic discriminant function analysis, logistic regression (LR) and a neural network. Wilk's regression analysis was performed to determine which variables influenced the model significantly. Of the four models investigated, LR and a neural network performed the best with receiver operating characteristic areas under the curve of 0.93 and 0.95, respectively, correlating to a sensitivity of 28% and a specificity of 99% for the LR model, and a sensitivity and specificity of 56 and 97% for the neural network model. Reverse regression yielded P-values for the testis volume and sperm density of
- Subjects :
- Male
Models, Statistical
Sperm Count
medicine.diagnostic_test
Receiver operating characteristic
Artificial neural network
business.industry
Urology
Regression analysis
Semen analysis
Endocrine System Diseases
Logistic regression
Regression
Odds
Andrology
Data set
Statistics
Sperm Motility
medicine
Humans
business
Infertility, Male
Forecasting
Retrospective Studies
Subjects
Details
- ISSN :
- 14765489 and 09559930
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- International Journal of Impotence Research
- Accession number :
- edsair.doi.dedup.....c2f6d4ac27a36462232e62e1442c69d0
- Full Text :
- https://doi.org/10.1038/sj.ijir.3901593