Providing a Prostate Cancer Detection and Prevention Method With Developed Deep Learning Approach.

Journal: Prostate cancer
Published Date: Jan 1, 2025

Abstract

Prostate cancer is the second most common cancer among men worldwide. This cancer has become extremely noticeable due to the increase of prostate cancer in Iranian men in recent years due to the lack of marriage and sexual intercourse, as well as the abuse of hormones in sports without any standards. The histopathology images from a treatment center to diagnose prostate cancer are used with the help of deep learning methods, considering the two characteristics of Tile and Grad-CAM. The approach of this research is to present a prostate cancer diagnosis model to achieve proper performance from histopathology images with the help of a developed deep learning method based on the manifold model. Similarly, in addition to the diagnosis of prostate cancer, a study on the methods of preventing this disease was investigated in literature reviews, and finally, after simulation, prostate cancer presentation factors were determined. The simulation results indicated that the proposed method has a performance advantage over the other state-of-the-art methods, and the accuracy of this method is up to 97.41%.

Authors

  • Alireza Zarei
    Department of Engineering, Faculty of Biomedical Engineering, Apadana Institute of Higher Education, Shiraz, Iran.
  • Elias Mazrooei Rad
    Biomedical Engineering Department, Khavaran Institute of Higher Education, Mashhad, Iran.
  • Shahryar Salmani Bajestani
    Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
  • Seyyed Ali Zendehbad
    Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals