Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems

Pennipat Nabheerong; Warissara Kiththiworaphongkich; Watcharaporn Cholamjiak

doi:10.1155/2023/2060375

Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems

Int J Breast Cancer. 2023 Sep 7:2023:2060375. doi: 10.1155/2023/2060375. eCollection 2023.

Authors

Pennipat Nabheerong¹, Warissara Kiththiworaphongkich², Watcharaporn Cholamjiak³

Affiliations

¹ Radiology Department, School of Medicine, University of Phayao, Phayao 56000, Thailand.
² Radiology Department, Phayao Hospital, Phayao 56000, Thailand.
³ School of Science, University of Phayao, Phayao 56000, Thailand.

Abstract

To detect breast cancer in mammography screening practice, we modify the inertial relaxed CQ algorithm with Mann's iteration for solving split feasibility problems in real Hilbert spaces to apply in an extreme learning machine as an optimizer. Weak convergence of the proposed algorithm is proved under certain mild conditions. Moreover, we present the advantage of our algorithm by comparing it with existing machine learning methods. The highest performance value of 85.03% accuracy, 82.56% precision, 87.65% recall, and 85.03% F1-score show that our algorithm performs better than the other machine learning models.