[This corrects the article DOI: 10.1371/journal.pone.0050093.].
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7098600 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231195 | PLOS |
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Individualized growth prediction of mice skin tumors with maximum likelihood estimators.
Comput Methods Programs Biomed
March 2020
School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou 15780, Athens, Greece. Electronic address:
Background & Objective: In this work, we focus on estimating the parameters of the Gompertz model in order to predict tumor growth. The estimation is based on measurements from mice skin tumors of de novo carcinogenesis. The main objective is to compare the Maximum Likelihood estimator with the best performance from our previous work with the Non-linear Least Squares estimator which is commonly used in the literature to estimate the growth parameters of the Gompertz model.
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