Cloud-Based Breast Cancer Prediction Empowered with Soft Computing Approaches
Joint Authors
Athar, Atifa
Hussain, Muhammad
Khan, Farrukh
Khan, Muhammad Adnan
Abbas, Sagheer
Siddiqui, Shahan Yamin
Khan, Abd al-Hannan
Saeed, Muhammad Anwaar
Source
Journal of Healthcare Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-19
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
The developing countries are still starving for the betterment of health sector.
The disease commonly found among the women is breast cancer, and past researches have proven results that if the cancer is detected at a very early stage, the chances to overcome the disease are higher than the disease treated or detected at a later stage.
This article proposed cloud-based intelligent BCP-T1F-SVM with 2 variations/models like BCP-T1F and BCP-SVM.
The proposed BCP-T1F-SVM system has employed two main soft computing algorithms.
The proposed BCP-T1F-SVM expert system specifically defines the stage and the type of cancer a person is suffering from.
Expert system will elaborate the grievous stages of the cancer, to which extent a patient has suffered.
The proposed BCP-SVM gives the higher precision of the proposed breast cancer detection model.
In the limelight of breast cancer, the proposed BCP-T1F-SVM expert system gives out the higher precision rate.
The proposed BCP-T1F expert system is being employed in the diagnosis of breast cancer at an initial stage.
Taking different stages of cancer into account, breast cancer is being dealt by BCP-T1F expert system.
The calculations and the evaluation done in this research have revealed that BCP-SVM is better than BCP-T1F.
The BCP-T1F concludes out the 96.56 percentage accuracy, whereas the BCP-SVM gives accuracy of 97.06 percentage.
The above unleashed research is wrapped up with the conclusion that BCP-SVM is better than the BCP-T1F.
The opinions have been recommended by the medical expertise of Sheikh Zayed Hospital Lahore, Pakistan, and Cavan General Hospital, Lisdaran, Cavan, Ireland.
American Psychological Association (APA)
Khan, Farrukh& Khan, Muhammad Adnan& Abbas, Sagheer& Athar, Atifa& Siddiqui, Shahan Yamin& Khan, Abd al-Hannan…[et al.]. 2020. Cloud-Based Breast Cancer Prediction Empowered with Soft Computing Approaches. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1186393
Modern Language Association (MLA)
Khan, Farrukh…[et al.]. Cloud-Based Breast Cancer Prediction Empowered with Soft Computing Approaches. Journal of Healthcare Engineering No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1186393
American Medical Association (AMA)
Khan, Farrukh& Khan, Muhammad Adnan& Abbas, Sagheer& Athar, Atifa& Siddiqui, Shahan Yamin& Khan, Abd al-Hannan…[et al.]. Cloud-Based Breast Cancer Prediction Empowered with Soft Computing Approaches. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1186393
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186393