Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

194
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

108
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

PREDICTION OF COLORECTAL CANCER TUMOR LOCATION USING DATA MINING

Pages

  154-163

Abstract

 Background: COLORECTAL CANCER is one of the most common cancers in terms of morbidity and mortality worldwide. A lot of research have been done in this field in Iran and worldwide, which have positive results. The aims of this study were firstly doing a statistical study on COLORECTAL CANCER in Mashhad, Iran, and finally PREDICTing the colorectal LOCATION of cancer based on the clinical data by using DATA MINING science and DECISION TREE model.Materials and Methods: The data of 316 patients with COLORECTAL CANCER (including 14 features) were extracted from the archive of Imam Reza Hospital, Mashhad. The instrument used in this research was Rapid Miner DATA MINING software that would try to be extract the details of the relevant data by statistical surveys and then would do initial simulations and the use of classification and DECISION TREE method have PREDICTeion the LOCATION of cancer.Results: Male to female ratio of 56% to 44%, family history of 37%, more young patients, and relatively more distally located cancers (39%) compared with the proximal (35%), and rectum (26%) were the striking findings of this study. The final and most important stage of research models were presented, which was able to PREDICT the LOCATION of the cancerous tumor with 80% accuracy.Conclusion: Similarities with global statistics, such as the ratio of men to women and family history were observed. But there were also differences with global statistics including the Iran’s younger patients and relatively more patients with distal cancers. The efficiency of DATA MINING techniques to PREDICT the LOCATION of cancer as well as cost reduction was among the most important results of this study.

Cites

  • No record.

    • References

  • No record.

    • Cite

    APA: Copy

    KHAKSHOOR, MOHAMMAD MAHDI, POURBADAKHSHAN, KAZEM, & GOSHAYESHI, LADAN. (2017). PREDICTION OF COLORECTAL CANCER TUMOR LOCATION USING DATA MINING. GOVARESH JOURNAL, 22(3), 154-163. SID. https://sid.ir/paper/701766/en

    Vancouver: Copy

    KHAKSHOOR MOHAMMAD MAHDI, POURBADAKHSHAN KAZEM, GOSHAYESHI LADAN. PREDICTION OF COLORECTAL CANCER TUMOR LOCATION USING DATA MINING. GOVARESH JOURNAL[Internet]. 2017;22(3):154-163. Available from: https://sid.ir/paper/701766/en

    IEEE: Copy

    MOHAMMAD MAHDI KHAKSHOOR, KAZEM POURBADAKHSHAN, and LADAN GOSHAYESHI, “PREDICTION OF COLORECTAL CANCER TUMOR LOCATION USING DATA MINING,” GOVARESH JOURNAL, vol. 22, no. 3, pp. 154–163, 2017, [Online]. Available: https://sid.ir/paper/701766/en

    Related Journal Papers

  • No record.

    • Related Seminar Papers

  • No record.

    • Related Plans

  • No record.

    • Recommended Workshops






    Move to top