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基于云计算的乳腺癌预测方法研究

Cloud-Based Breast Cancer Prediction Empowered with Soft Computing Approaches.

机构信息

Department of Computer Science, National College of Business Administration and Economics, Lahore, Pakistan.

Department of Computer Science, Lahore Institute of Science and Technology, Lahore, Pakistan.

出版信息

J Healthc Eng. 2020 May 18;2020:8017496. doi: 10.1155/2020/8017496. eCollection 2020.

Abstract

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 with 2 variations/models like and . The proposed 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 is better than . The concludes out the 96.56 percentage accuracy, whereas the gives accuracy of 97.06 percentage. The above unleashed research is wrapped up with the conclusion that is better than the . The opinions have been recommended by the medical expertise of Sheikh Zayed Hospital Lahore, Pakistan, and Cavan General Hospital, Lisdaran, Cavan, Ireland.

摘要

发展中国家仍在努力改善医疗保健领域。在女性中常见的疾病是乳腺癌,过去的研究已经证明,如果在早期发现癌症,战胜疾病的机会高于晚期治疗或发现的癌症。本文提出了基于云的智能,有 2 种变化/模型,如和。所提出的系统采用了两种主要的软计算算法。所提出的 BCP-T1F-SVM 专家系统专门定义了一个人患有疾病的阶段和类型。专家系统将详细说明癌症的严重阶段,以及患者所遭受的程度。所提出的 BCP-SVM 提高了所提出的乳腺癌检测模型的精度。在乳腺癌的突出问题中,所提出的 BCP-T1F-SVM 专家系统给出了更高的精度率。所提出的 BCP-T1F 专家系统用于诊断乳腺癌的早期阶段。考虑到不同的癌症阶段,BCP-T1F 专家系统正在处理乳腺癌。该研究中的计算和评估表明,优于。结论得出 96.56%的准确率,而准确率为 97.06%。上述研究得出的结论是优于。这一观点得到了巴基斯坦拉合尔谢赫扎耶德医院和爱尔兰卡万的卡万综合医院的医学专家的推荐。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d402/7254089/8176c3d983ba/JHE2020-8017496.001.jpg

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