The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Artificial Intelligence in Early Breast Cancer Screening: A New Frontier
|
|
Author(s): Shaheen Layaq (Singareni Collieries Women's Degree and PG College, India), S. K. Parvez Ahammad (Kavitha Memorial Degree College, India)and Pakalapati Arpitha (Telangana Social Welfare Residential Degree College for Women, India)
Copyright: 2026
Pages: 32
Source title:
AI and Machine Learning for Cancer Care: Precision Medicine and Beyond
Source Author(s)/Editor(s): Manvi Mishra (Shri Ram Murti Smarak College of Engineering and Technology, Bareilly, India), Piyush Kumar (Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly, India), Himanshi Khattar (Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly, India)and Mohammad Zubair Khan (Islamic University of Madinah, Saudi Arabia)
DOI: 10.4018/979-8-3373-4312-9.ch006
Purchase
|
Abstract
Breast cancer is a kind of malignant tumor that mostly found in women which grows around the tissue of breast. During the process of diagnosis the cancer cells and non cancer cells are been identified and their count is made. If the count of cancer cells is greater than non cancer cells then the patient undergoes the treatments. The early detection of breast cancer can save the life of patient. Now a day's AI is playing a vital role in classifying cancer and non cancer cells in a accurate way. Many of the earlier researchers had performed the work of classifying them but, most of them lack in the accuracy. To have good accuracy a new method EBCS (Early Breast Cancer Screening) is proposed which consists of four steps or phases- preprocessing, classifying, performance evaluation and providing clear understanding to human.. To implement the four steps python programming is been used and cancer data set was extracted from Breast Cancer Wisconsin (Diagnostic) data set. The proposed method EBCS gave an accuracy of 99 percentage and complexity is also reduced.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|