Neural modelling of growth hormone therapy for the prediction of therapy results

• Autorzy: Smyczyńska U. , Smyczyńska J. , Tadeusiewicz R.

Identyfikatory

DOI

10.1515/bams-2014-0021

• Języki publikacji: EN

Abstrakty

EN

In this paper, we presented the problem of predicting response to recombinant human growth hormone (GH) treatment in GH-deficient children. Such a prediction can be done by techniques of mathematical modelling and is important because the therapy consists of daily injections and is expensive; thus, it should be administered only to those patients who will, with high probability, benefit from it. Until now, the leading methodological approach to this problem was multiple regression analysis. Several authors demonstrated that it is possible to derive useful models by this method; however, it has some obvious limitations that can be avoided with the use of the proposed neural network approach.

Słowa kluczowe

EN

growth hormone; neural networks; therapy result prediction

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; Index Copernicus Sp. z o.o.
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2015
• Tom: Vol. 11, no. 1
• Strony: 33--45
• Opis fizyczny: Bibliogr. 24 poz., rys., wykr.

Twórcy

autor

Smyczyńska U.

• Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Cracow 30-059, Poland

autor

Smyczyńska J.

• Department of Endocrinology and Metabolic Diseases, Polish Mothers’ Memorial Hospital-Research Institute in Lodz, Lodz 93-338, Poland

autor

Tadeusiewicz R.

• Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Cracow 30-059, Poland

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