Breast Cancer Detection Techniques: A Review

Authors

  • Manar AL-Mahdawi Department of Medical Physics, College of Science, Al-Nahrain University, Baghdad, Iraq
  • Nabeel Mubarak Mirza Department of Physics, College of Education, Mustansiriyah University, Baghdad, Iraq
  • Mohammed Y. Kamil College of Science, Mustansiriyah University, Baghdad, Iraq

DOI:

https://doi.org/10.22401/djy0sb09

Keywords:

Breast Cancer , Diagnosis , Machine learning , Deep learning , Detection , Artificial Intelligent

Abstract

Breast cancer is an important global health issue affecting women, leading to death. Early detection is the best way to improve detection and survival rates. Deep learning (DL) and machine learning (ML) approaches have shown good results in detecting breast cancer. This study reviews ML and DL techniques, discussing their applications in medical image data like mammograms and histopathological images. This paper clarifies the challenges and limitations of detection techniques and clinical validation for successful implementation in real-world healthcare. The findings of this review are valuable for researchers and clinicians in terms of the usefulness of these technologies for detecting breast cancer.

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Published

2024-12-15

How to Cite

(1)
Breast Cancer Detection Techniques: A Review. ANJS 2024, 27 (5), 105-113. https://doi.org/10.22401/djy0sb09.