Artificial neural network for predicting pathological stage of clinically localized prostate cancer in a Taiwanese population.

@article{Tsao2014ArtificialNN,
  title={Artificial neural network for predicting pathological stage of clinically localized prostate cancer in a Taiwanese population.},
  author={C. W. V. Tsao and Ching-Yu Liu and T L Cha and Sheng-Tang Wu and Guang-Huan Sun and Dah-Shyong Yu and Hong-I Chen and S Chang and S P Chen and Chien-Yeh Hsu},
  journal={Journal of the Chinese Medical Association : JCMA},
  year={2014},
  volume={77 10},
  pages={513-8}
}
BACKGROUND We developed an artificial neural network (ANN) model to predict prostate cancer pathological staging in patients prior to when they received radical prostatectomy as this is more effective than logistic regression (LR), or combined use of age, prostate-specific antigen (PSA), body mass index (BMI), digital rectal examination (DRE), trans-rectal ultrasound (TRUS), biopsy Gleason sum, and primary biopsy Gleason grade. METHODS Our study evaluated 299 patients undergoing retro-pubic… CONTINUE READING
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