Precision and Progress: A 97% Accurate Model for Breast Cancer Detection

Registration ID: IJNRD_211033

Published ID: IJNRD2312205

DOI: Click Here to Get

Karthik Reddy Munnangi , Jampala Venkata Saileenath Reddy , Sai Ruthvik Reddy Aella , Kalipindi Navya , Dr. S Sri Harsha

Deep learning, Breast cancer, machine learning, Cancer, Diagnosis

The present research study explores recent breakthroughs in the domain of breast cancer diagnosis, specifically emphasising the use of advanced deep learning algorithms. The escalating rise in breast cancer prevalence in India, characterised by the diagnosis of one woman with the ailment every two minutes and the mortality of one woman every nine minutes, highlights the pressing need for more accurate and effective diagnostic techniques. In contrast to traditional methodologies, our distinctive methodology leverages the capabilities of machine learning, resulting in a notable accuracy rate of 97%. This paper provides a complete examination of the use of deep learning and machine learning algorithms for the purpose of identifying and categorising breast cancer. This study especially focuses on the detection and differentiation of dense masses, tumours, and non-tumorous areas using several medical imaging modalities. The paper comprehensively covers several machine learning approaches, deep learning algorithms, and specialized neural network designs designed specifically for accurate diagnosis and classification of breast cancer. Furthermore, the study presents a thorough examination of the various imaging modalities and research databases that are accessible for the purposes of training and validation. This research further explores prospective advancements and challenges within the realm of breast cancer detection and therapy, emphasising the crucial significance of precise and effective detection techniques in addressing this pressing matter of public health. This study not only makes a valuable contribution to the area of medical science, but also underscores the need of early identification and diagnosis, eventually resulting in improved outcomes for individuals with breast cancer.

Published Paper   E-Certificate

Karthik Reddy Munnangi, Jampala Venkata Saileenath Reddy , Sai Ruthvik Reddy Aella, Kalipindi Navya, & Dr. S Sri Harsha (December-2023). Precision and Progress: A 97% Accurate Model for Breast Cancer Detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(12), c46-c51. https://ijnrd.org/papers/IJNRD2312205.pdf

Volume 8 Issue 12, December-2023

Pages : c46-c51

Paper Reg. ID: IJNRD_211033

Published Paper Id: IJNRD2312205

Downloads: 000121982

Research Area: Engineering

Country: Vijayawada, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2312205.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2312205

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details