The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Breast Cancer Detection Using Machine Learning: A New Frontier in Early Diagnosis
|
|
Author(s): Priyanka Pradhan (Regional College of Professional Studies and Research, India), Afshan Zameer (Rakshpal Bahadur Management Institute, India), Manvi Mishra (SRMS College of Engineering Technology and Research, Bareilly, India)and Kirti Seth (School of Computer Science and Engineering, INHA University, Tashkent, Uzbekistan)
Copyright: 2026
Pages: 38
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.ch004
Purchase
|
Abstract
Breast cancer remains one of the most widespread and life-threatening diseases affecting women worldwide. The early detection and accurate diagnosis of breast cancer are crucial for reducing death rates and improving patient outcomes. Machine learning (ML), a subset of artificial intelligence, has recently emerged as a powerful tool in the healthcare sector, offering promising solutions to the challenges posed by traditional diagnostic methods. This chapter aims to present a comprehensive exploration of how machine learning techniques can revolutionize the process of breast cancer detection and classification. It delves into a wide array of ML algorithms, data acquisition techniques, feature extraction, model evaluation metrics, and real-world implementation challenges, providing a solid theoretical and practical foundation for researchers, practitioners, and students. The vision is to create a holistic and accessible resource that not only informs but also inspires further innovation in the use of ML for breast cancer detection.
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.
|
|
|