@inbook{1ba9e9b55b834d20a0c4f31cfc46eea1,
title = "Mathematically modelling hCG in women with gestational trophoblastic disease using logarithmic transformations",
abstract = "Transformations are a common technique used to linearize data so that simple linear regression can be applied. A common transformation used is the logarithmic transformation. This transforms data that follows an exponential pattern so that a straight line can be fit to it. In this study human chorionic gonadotropin (hCG) levels in women with gestational trophoblastic disease (GTD), which are known to decrease exponentially, are transformed using a logarithmic transformation and the line of best fit is found. A new method is then described including vertical shift in the model. The two methods are tested on data provided by the National Center for GTD in Cork University Maternity Hospital. It was found that the new method described here was more accurate at predicting future hCG measurements.",
keywords = "Gestational trophoblastic disease, HCG, Logarithmic transformation, Mathematical modelling",
author = "Catherine Costigan and Sabin Tabirca and John Coulter",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 18th UKSim-AMSS International Conference on Computer Modelling and Simulation, UKSim 2016 ; Conference date: 06-04-2016 Through 08-04-2016",
year = "2016",
month = dec,
day = "22",
doi = "10.1109/UKSim.2016.60",
language = "English",
series = "Proceedings - 2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation, UKSim 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "55--59",
editor = "Glenn Jenkins and David Al-Dabass and Alessandra Orsoni and Richard Cant",
booktitle = "Proceedings - 2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation, UKSim 2016",
address = "United States",
}