Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach
Background and Aim: Gastric cancer is the second leading cause of cancer death in the world. Due to the prevalence of the disease and the high mortality rate of gastric cancer in Iran, the factors affecting the development of this disease should be taken into account. In this research, two data mini...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
Tehran University of Medical Sciences
2017-09-01
|
| Series: | پیاورد سلامت |
| Subjects: | |
| Online Access: | http://payavard.tums.ac.ir/article-1-6295-en.html |
| _version_ | 1831765129038921728 |
|---|---|
| author | Seyed Abbas Mahmoodi Kamal Mirzaie Seyed Mostafa Mahmoodi |
| author_facet | Seyed Abbas Mahmoodi Kamal Mirzaie Seyed Mostafa Mahmoodi |
| author_sort | Seyed Abbas Mahmoodi |
| collection | DOAJ |
| description | Background and Aim: Gastric cancer is the second leading cause of cancer death in the world. Due to the prevalence of the disease and the high mortality rate of gastric cancer in Iran, the factors affecting the development of this disease should be taken into account. In this research, two data mining techniques such as Apriori and ID3 algorithm were used in order to investigate the effective factors in gastric cancer.
Materials and Methods: Data sets in this study were collected among 490 patients including 220 patients with gastric cancer and 270 healthy samples referred to Imam Reza hospital in Tabriz. The best rules related to this data set were extracted through Apriori algorithm and implementing it in MATLAB. ID3 algorithm was also used to investigate these factors.
Results: The results showed that having a history of gastro esophageal reflux has the greatest impact on the incidence of this disease. Some rules extracted through Apriori algorithm can be a model to predict patient status and the incidence of the disease and investigate factors affecting the disease. The prediction accuracy achieved through ID3 algorithm is 85.56 which was a very good result in the prediction of gastric cancer.
Conclusion: Using data mining, especially in medical data, is very useful due to the large volume of data and unknown relationships between systemic, personal, and Behavioral Features of patients. The results of this study could help physicians to identify the contributing factors in incidence of the disease and predict the incidence of the disease. |
| first_indexed | 2024-12-22T05:56:52Z |
| format | Article |
| id | doaj.art-fb9f865a0dc048c9aba7822fdc9b485f |
| institution | Directory Open Access Journal |
| issn | 1735-8132 2008-2665 |
| language | fas |
| last_indexed | 2024-12-22T05:56:52Z |
| publishDate | 2017-09-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | پیاورد سلامت |
| spelling | doaj.art-fb9f865a0dc048c9aba7822fdc9b485f2022-12-21T18:36:42ZfasTehran University of Medical Sciencesپیاورد سلامت1735-81322008-26652017-09-01113332341Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining ApproachSeyed Abbas Mahmoodi0Kamal Mirzaie1Seyed Mostafa Mahmoodi2 Master of Science in Computer Engineering, Computer Engineering Department, School of Engineering, Islamic Azad University, Yazd Branch, Yazd, Iran Assistant Professor, Computer Engineering Department, School of Engineering, Islamic Azad University, Maybod Branch, Maybod, Iran Assistant Professor, Oral Pathology Department, School of Dentistry, Shahid Sadoughi University of Medical Sciences, Yazd, Iran Background and Aim: Gastric cancer is the second leading cause of cancer death in the world. Due to the prevalence of the disease and the high mortality rate of gastric cancer in Iran, the factors affecting the development of this disease should be taken into account. In this research, two data mining techniques such as Apriori and ID3 algorithm were used in order to investigate the effective factors in gastric cancer. Materials and Methods: Data sets in this study were collected among 490 patients including 220 patients with gastric cancer and 270 healthy samples referred to Imam Reza hospital in Tabriz. The best rules related to this data set were extracted through Apriori algorithm and implementing it in MATLAB. ID3 algorithm was also used to investigate these factors. Results: The results showed that having a history of gastro esophageal reflux has the greatest impact on the incidence of this disease. Some rules extracted through Apriori algorithm can be a model to predict patient status and the incidence of the disease and investigate factors affecting the disease. The prediction accuracy achieved through ID3 algorithm is 85.56 which was a very good result in the prediction of gastric cancer. Conclusion: Using data mining, especially in medical data, is very useful due to the large volume of data and unknown relationships between systemic, personal, and Behavioral Features of patients. The results of this study could help physicians to identify the contributing factors in incidence of the disease and predict the incidence of the disease.http://payavard.tums.ac.ir/article-1-6295-en.htmldata miningassociation rulesapriori algorithmgastric cancerid3 algorithm |
| spellingShingle | Seyed Abbas Mahmoodi Kamal Mirzaie Seyed Mostafa Mahmoodi Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach پیاورد سلامت data mining association rules apriori algorithm gastric cancer id3 algorithm |
| title | Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach |
| title_full | Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach |
| title_fullStr | Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach |
| title_full_unstemmed | Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach |
| title_short | Determining the Effective Factors in the Incidence of Gastric Cancer by Using Data Mining Approach |
| title_sort | determining the effective factors in the incidence of gastric cancer by using data mining approach |
| topic | data mining association rules apriori algorithm gastric cancer id3 algorithm |
| url | http://payavard.tums.ac.ir/article-1-6295-en.html |
| work_keys_str_mv | AT seyedabbasmahmoodi determiningtheeffectivefactorsintheincidenceofgastriccancerbyusingdataminingapproach AT kamalmirzaie determiningtheeffectivefactorsintheincidenceofgastriccancerbyusingdataminingapproach AT seyedmostafamahmoodi determiningtheeffectivefactorsintheincidenceofgastriccancerbyusingdataminingapproach |