UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 9 | September 2025

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Published in:

Volume 12 Issue 9
September-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2509444


Registration ID:
569667

Page Number

e389-e396

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Title

Meta-Analysis Review on Machine Learning and Deep Learning Applications in Breast Cancer Detection

Abstract

Many women worldwide are still affected by breast cancer which is known to be both widespread and dangerous. Finding it at an early stage is very important for saving more lives and making treatments more successful. Lately, the growth in AI, specifically in machine learning (ML) and deep learning (DL) technologies, has greatly affected the way medical diagnostics are carried out. They depend on computer-based models that can detect faint trends in broad and complicated groups of data which may include X-ray and ultrasound images, medical records and DNA codes. It brings together insights from 50 recent articles on ML and DL which discuss their role in detecting, classifying and predicting breast cancer. Review makes clear how AI studies are completed on various machine learning algorithms, using various medical databases and applied to different clinical needs. Studies have confirmed that deep learning, mainly convolutional neural networks (CNNs), are favored because they are made to learn from large multidimensional data. Nevertheless, support vector machines (SVMs), decision trees and ensemble methods are used widely, mainly in situations where processes or data follow typical structures. It also points out new research approaches, obstacles in data (like unequal numbers of samples) and an increasing interest in getting models to work on new, unseen data. Pulling together these insights, the meta-analysis wants to shape future breast cancer studies and help apply AI technology in patient care.

Key Words

Breast Cancer Detection, Machine Learning, Deep Learning, Meta-Analysis, Imaging, Clinical Data, CNN, AI in Healthcare

Cite This Article

"Meta-Analysis Review on Machine Learning and Deep Learning Applications in Breast Cancer Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.e389-e396, September-2025, Available :http://www.jetir.org/papers/JETIR2509444.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Meta-Analysis Review on Machine Learning and Deep Learning Applications in Breast Cancer Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppe389-e396, September-2025, Available at : http://www.jetir.org/papers/JETIR2509444.pdf

Publication Details

Published Paper ID: JETIR2509444
Registration ID: 569667
Published In: Volume 12 | Issue 9 | Year September-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/jetir.v12i9.569667
Page No: e389-e396
Country: Naihati, West Bengal, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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