Name
Abstract | ||
|---|---|---|
Modeling the tumor behavior in the host organ as function of time and radiation dose has been a major study in the previous decades. Here the effort in estimation of cancerous and normal cell proliferation and growth in glioblastoma multiform (GBM) tumor is presented. This paper introduces a new mathematical model in the form of differential equation of tumor growth. The model contains dose delivery amount in the treatment scheme as an input term. It also can be utilized to optimize the treatment process in order to increase the patient survival period. Gene expression programming (GEP) as a newconcept is used for estimating this model. The LQ model has also been applied to GEP as an initial value, causing acceleration and improvement of the algorithm estimation. The model shows the number of the tumor and normal brain cells during the treatment process using the status of normal and cancerous cells in the initiation of treatment, the timing and amount of dose delivery to the patient, and a coefficient that describes the brain condition. A critical level is defined for normal cell when the patient's death occurs. In the end the model has been verified by clinical data obtained from previous accepted formulae and some of our experimental resources. The proposed model helps to predict tumor growth during treatment process in which further treatment processes can be controlled. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1155/2014/481935 | COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE |
Field | DocType | Volume |
Oncology,Gene expression programming,Glioblastoma,Radiation dose,Internal medicine,Computer science,Brain condition,Artificial intelligence,Machine learning | Journal | 2014 |
ISSN | Citations | PageRank |
1748-670X | 0 | 0.34 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Jamali Nazari | 1 | 0 | 0.34 |
| Dariush Sardari | 2 | 0 | 0.34 |
| Ahmad Reza Vali | 3 | 3 | 1.08 |
| Keivan Maghooli | 4 | 1 | 4.08 |