Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Breast cancer is a significant global health concern, accounting for a large number of cancer-related deaths among women. Timely and accurate diagnosis is critical to improving treatment outcomes and patient survival rates. The complexity and volume of breast cancer data, however, present challenges in effective diagnosis using traditional methods. This research explores the application of machine learning (ML) techniques to simplify, analyze, and derive meaningful insights from breast cancer datasets.
"A Study-Oriented Analysis of Simplifying Breast Cancer Data Using Machine Learning Approaches", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 8, page no.a622-a630, August-2025, Available :http://www.ijrti.org/papers/IJRTI2508076.pdf
Downloads:
000721
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator