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Application of gene expression programming and sensitivity analyses in analyzing effective parameters in gastric cancer tumor size and location

  • Shadi Dorosti
  • Saeid Jafarzadeh Ghoushchi
  • Elham Sobhrakhshankhah
  • Mohsen AhmadiEmail author
  • Abbas Sharifi
Methodologies and Application
  • 2 Downloads

Abstract

Gastric cancer (GC) is the third reason for cancer-related deaths in the world. The late referral of patients to medical centers in an advanced stage can make the treatment procedure more difficult. Accurate diagnosis of risk factors in GC tumor size and tumor location can lead to taking preventive measures or determining a suitable treatment strategy. This study aims to present a general model to identify the correlation of different parameters in a GC tumor place and tumor size. The medical documents of GC patients consist of the dataset of this study. The effect of seven main parameters, namely age, smoking, Helicobacter pylori (H. pylori) infection, job, surgical background, sex, and nodal stage is investigated in GC tumor location and tumor size. By considering all the medical documents, data modeling is conducted using gene expression programming because of the high precision of model output. In the following, three different sensitivity analysis methods (Morris, Distributed Evaluation of Local Sensitivity Analysis (DELSA), and Sobol’–Jansen) are applied to determine the influential factors in the tumor size and location. Results show that in sequence, sex, age, and H. pylori records mostly affect tumor location; the nodal stage, smoking, and surgery record mostly affect tumor size. This method can help in identifying effective parameters and prevention of patients’ death in all types of diseases, even for terminal illnesses.

Keywords

Gastric cancer Sensitivity analysis Gene expression programming Sobol’–Jansen Morris Distributed Evaluation of Local Sensitivity Analysis 

Notes

Funding

The funding sources had no involvement in the study design, collection, analysis or interpretation of data, writing of the manuscript or in the decision to submit the manuscript for publication.

Compliance with ethical standards

Conflict of interest

Authors have no conflict of interest.

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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Industrial EngineeringUrmia University of Technology (UUT)UrmiaIran
  2. 2.Department of Internal Medicine, Imam Khomeini HospitalUrmia University of Medical ScienceUrmiaIran
  3. 3.Department of Mechanical EngineeringUrmia University of Technology (UUT)UrmiaIran

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