Stochastic Gompertzian model for breast cancer growth process

In this paper, a stochastic Gompertzian model is developed to describe the growth process of a breast cancer by incorporating the noisy behavior into a deterministic Gompertzian model. The prediction quality of the stochastic Gompertzian model is measured by comparing the simulated result with the c...

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Main Authors: Mazma Syahidatul Ayuni, Mazlan, Norhayati, Rosli
Format: Conference or Workshop Item
Language:English
Published: AIP Publishing 2017
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/21977/1/Stochastic%20Gompertzian%20model%20for%20breast%20cancer%20growth%20process1.pdf
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author Mazma Syahidatul Ayuni, Mazlan
Norhayati, Rosli
author_facet Mazma Syahidatul Ayuni, Mazlan
Norhayati, Rosli
author_sort Mazma Syahidatul Ayuni, Mazlan
collection UMP
description In this paper, a stochastic Gompertzian model is developed to describe the growth process of a breast cancer by incorporating the noisy behavior into a deterministic Gompertzian model. The prediction quality of the stochastic Gompertzian model is measured by comparing the simulated result with the clinical data of breast cancer growth. The kinetic parameters of the model are estimated via maximum likelihood procedure. 4-stage stochastic Runge-Kutta (SRK4) is used to simulate the sample path of the model. Low values of mean-square error (MSE) of stochastic model indicate good fits. It is shown that the stochastic Gompertzian model is adequate in explaining the breast cancer growth process compared to the deterministic model counterpart
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spelling UMPir219772018-09-05T04:00:31Z http://umpir.ump.edu.my/id/eprint/21977/ Stochastic Gompertzian model for breast cancer growth process Mazma Syahidatul Ayuni, Mazlan Norhayati, Rosli QA Mathematics In this paper, a stochastic Gompertzian model is developed to describe the growth process of a breast cancer by incorporating the noisy behavior into a deterministic Gompertzian model. The prediction quality of the stochastic Gompertzian model is measured by comparing the simulated result with the clinical data of breast cancer growth. The kinetic parameters of the model are estimated via maximum likelihood procedure. 4-stage stochastic Runge-Kutta (SRK4) is used to simulate the sample path of the model. Low values of mean-square error (MSE) of stochastic model indicate good fits. It is shown that the stochastic Gompertzian model is adequate in explaining the breast cancer growth process compared to the deterministic model counterpart AIP Publishing 2017 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21977/1/Stochastic%20Gompertzian%20model%20for%20breast%20cancer%20growth%20process1.pdf Mazma Syahidatul Ayuni, Mazlan and Norhayati, Rosli (2017) Stochastic Gompertzian model for breast cancer growth process. In: AIP Conference Proceedings: The 3rd ISM International Statistical Conference 2016 (ISM-III) , 9-11 August 2016 , Kuala Lumpur, Malaysia. pp. 1-7., 1842 (030013). ISSN 0094-243X ISBN 978-0-7354-1512-6 (Published) http://dx.doi.org/10.1063/1.4982851
spellingShingle QA Mathematics
Mazma Syahidatul Ayuni, Mazlan
Norhayati, Rosli
Stochastic Gompertzian model for breast cancer growth process
title Stochastic Gompertzian model for breast cancer growth process
title_full Stochastic Gompertzian model for breast cancer growth process
title_fullStr Stochastic Gompertzian model for breast cancer growth process
title_full_unstemmed Stochastic Gompertzian model for breast cancer growth process
title_short Stochastic Gompertzian model for breast cancer growth process
title_sort stochastic gompertzian model for breast cancer growth process
topic QA Mathematics
url http://umpir.ump.edu.my/id/eprint/21977/1/Stochastic%20Gompertzian%20model%20for%20breast%20cancer%20growth%20process1.pdf
work_keys_str_mv AT mazmasyahidatulayunimazlan stochasticgompertzianmodelforbreastcancergrowthprocess
AT norhayatirosli stochasticgompertzianmodelforbreastcancergrowthprocess