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

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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.

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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.

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Authors and Affiliations

  1. Department of Industrial Engineering, Urmia University of Technology (UUT), P.O. Box 57166-419, Urmia, Iran

    Shadi Dorosti, Saeid Jafarzadeh Ghoushchi & Mohsen Ahmadi

  2. Department of Internal Medicine, Imam Khomeini Hospital, Urmia University of Medical Science, Urmia, Iran

    Elham Sobhrakhshankhah

  3. Department of Mechanical Engineering, Urmia University of Technology (UUT), Urmia, Iran

    Abbas Sharifi

Authors
  1. Shadi Dorosti
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  2. Saeid Jafarzadeh Ghoushchi
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  3. Elham Sobhrakhshankhah
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  4. Mohsen Ahmadi
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  5. Abbas Sharifi
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Correspondence to Mohsen Ahmadi.

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Communicated by V. Loia.

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Dorosti, S., Jafarzadeh Ghoushchi, S., Sobhrakhshankhah, E. et al. Application of gene expression programming and sensitivity analyses in analyzing effective parameters in gastric cancer tumor size and location. Soft Comput 24, 9943–9964 (2020). https://doi.org/10.1007/s00500-019-04507-0

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