CNN-based deep learning approach for classification of invasive ductal and metastasis types of breast carcinoma.

Journal: Cancer medicine
PMID: 39215495

Abstract

OBJECTIVE: Breast cancer is one of the leading cancer causes among women worldwide. It can be classified as invasive ductal carcinoma (IDC) or metastatic cancer. Early detection of breast cancer is challenging due to the lack of early warning signs. Generally, a mammogram is recommended by specialists for screening. Existing approaches are not accurate enough for real-time diagnostic applications and thus require better and smarter cancer diagnostic approaches. This study aims to develop a customized machine-learning framework that will give more accurate predictions for IDC and metastasis cancer classification.

Authors

  • Tobibul Islam
    Department of Biomedical Engineering, Military Institute of Science and Technology, Dhaka, Bangladesh.
  • Md Enamul Hoque
    Department of Biomedical Engineering, Military Institute of Science and Technology, Dhaka, Bangladesh.
  • Mohammad Ullah
    Center for Advance Intelligent Materials, Universiti Malaysia Pahang, Kuantan, Malaysia.
  • Toufiqul Islam
    Department of Surgery, M Abdur Rahim Medical College, Dinajpur, Bangladesh.
  • Nabila Akter Nishu
    Department of Medicine, Armed Forces Medical College, Dhaka, Bangladesh.
  • Rabiul Islam
    Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, USA.

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