International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Transforming Breast Cancer Detection: AI as a Catalyst for Enhanced Clinical Outcomes

Author(s) Saikiran Rallabandi
Country United States
Abstract A revolutionary development in contemporary healthcare, especially in oncology, is the application of
artificial intelligence (AI) to breast cancer diagnosis. The use of AI-powered diagnostic tools in breast
cancer screening programs is examined in detail in this article, which shows notable gains in workflow
efficiency, accuracy, and early detection. Along with quantitative performance indicators and system
reliability measures, it examines the technological framework, which includes deep learning architectures
and integration workflows. Through a thorough analysis of data processing issues, fixes, and clinical
implications, the article shows how AI enhances radiologists' skills without replacing human knowledge.
It also discusses future technological advancements and scaling issues, emphasizing the possibility of
integrating multi-modal imaging and improving predictive capacities. This approach makes a strong case
for wider deployment across healthcare systems and is a blueprint for future AI integration in medical
diagnostics.
Keywords Keywords: AI-Powered Mammography, Breast Cancer Detection, Deep Learning Architecture, Clinical Workflow Optimization, Healthcare System Integration
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-05
Cite This Transforming Breast Cancer Detection: AI as a Catalyst for Enhanced Clinical Outcomes - Saikiran Rallabandi - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32241
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.32241
Short DOI https://doi.org/g8t3kj
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