Neural network models - a novel tool for predicting the efficacy of growth hormone (GH) therapy in children with short stature.

Journal: Neuro endocrinology letters
PMID: 26454490

Abstract

INTRODUCTION: The leading method for prediction of growth hormone (GH) therapy effectiveness are multiple linear regression (MLR) models. Best of our knowledge, we are the first to apply artificial neural networks (ANN) to solve this problem. For ANN there is no necessity to assume the functions linking independent and dependent variables. The aim of study is to compare ANN and MLR models of GH therapy effectiveness.

Authors

  • Joanna Smyczynska
    Department of Endocrinology and Metabolic Diseases, Polish Mother's Memorial Hospital - Research Institute, Lodz, Poland.
  • Maciej Hilczer
    Department of Endocrinology and Metabolic Diseases, Polish Mother's Memorial Hospital - Research Institute, Lodz, Poland.
  • Urszula Smyczynska
    AGH University of Science and Technology, Department of Automatics and Biomedical Engineering, Krakow, Poland.
  • Renata Stawerska
    Department of Endocrinology and Metabolic Diseases, Polish Mother's Memorial Hospital - Research Institute, Lodz, Poland.
  • Ryszard Tadeusiewicz
    AGH University of Science and Technology, Department of Automatics and Biomedical Engineering, Krakow, Poland.
  • Andrzej Lewinski
    Department of Endocrinology and Metabolic Diseases, Polish Mother's Memorial Hospital - Research Institute, Lodz, Poland.

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