Reliable Breast Cancer Diagnosis with Deep Learning: DCGAN-Driven Mammogram Synthesis and Validity Assessment

Breast cancer imaging is paramount to quickly detecting and accurately evaluating the disease. The scarcity of annotated mammogram data presents a significant obstacle when building deep learning models that can produce reliable outcomes. This paper proposes a novel approach that utilizes deep convo...

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Veröffentlicht in:Applied Computational Intelligence and Soft Computing Jg. 2024; H. 1
Hauptverfasser: Shah, Dilawar, Ullah Khan, Mohammad Asmat, Abrar, Mohammad
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Hindawi 2024
John Wiley & Sons, Inc
Wiley
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ISSN:1687-9724, 1687-9732
Online-Zugang:Volltext
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