Highlights

  • ISSN Number : 2584-0673

  • Four Issues Per Year

  • No Publication Fee 

  • Free and Open Access Peer Reviewed Journal  

  • Articles Invited in English only 

  • Submission to a Final Decision: 45 Days

  • Acceptance to Publication: 12 Days

Track manuscript
Enter only the numeric value. (eg. Enter 2014000001, not IJIMSR2014000001) and click on Track
Abstract
Early Prediction of Breast Cancer Risks Using Convolutional Neural Network - Volume -1 | Issue - 1 | 2023, (July'23 - Sep'23 )

Pages:73-80

Category: Engineering & Technology

Published Date: 20-Sep-2023

Dr. D Jaya Kumari, K Praveen Kumar

Keywords:

Deep Learning, Artificial Intelligence, Breast Cancer

Abstract:
Breast Cancer is one of the deadliest diseases in the world, among cancer categories, early detection is essential to better treatment outcomes and survival rates. Delay in diagnosis due to medical mistakes or incorrect interpretation of patient reports might have a negative effect on patient outcomes.Artificial intelligence (AI), a component of contemporary technology, has demonstrated encouraging potential for helping medical practitioners to increase the precision and effectiveness of cancer diagnosis. AI programs can be trained to examine several kinds of medical imaging data, including MRI and CT scans, and help spot anomalies or malignant cells. The study aims to establish a model for estimating the risk of breast cancer based on a combination of medical and behavior-related risk factors. The goal is to identify high-risk groups of patients who have undergone breast cancer surgery so that they can receive closer monitoring and more accurate screening.In this proposed work,we try to use CNN Model for classifying the risk of breast cancer.
Announcements

Call for Paper

Next Issue

Last Date : 15th November 2024

Search Articles

Indexed and Abstracted in

11_images.png
13_o7.png
14_o4.png
16_Open_Access_logo_with_dark_text_for_contrast,_on_transparent_background.png
17_ORCID_full_logo.png