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Deep Learning Cascaded Feature Selection Framework for Breast Cancer Classification: Hybrid CNN with Univariate-Based Approach

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Outgoing claims: the papers this work cites, builds on, or argues with.

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inferredcites →https://doi.org/10.1088/1361-6560/aa93d4openalex-snapshot
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inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
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inferredcites →https://doi.org/10.1109/icsee.2018.8646252openalex-snapshot
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inferredcites →https://doi.org/10.1109/iwssip.2019.8787295openalex-snapshot
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inferredcites →https://doi.org/10.21595/mme.2020.21552openalex-snapshot
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inferredcites →https://doi.org/10.3322/caac.21660openalex-snapshot
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inferredcites →https://doi.org/10.3348/kjr.2020.1210openalex-snapshot
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inferredcites →https://doi.org/10.3390/diagnostics9040165openalex-snapshot
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inferredcites →https://doi.org/10.3390/e23101251openalex-snapshot
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inferredcites →https://doi.org/10.3390/electronics9030445openalex-snapshot
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inferredcites →https://doi.org/10.3390/healthcare10081592openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A new univariate feature selection algorithm based on the best–worst multi-attribute decision-making method
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The Influence of Image Cropping Sizes on Mammographic Breast Cancer Classification Using CNN
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Systematic Review of Contemporary Breast Cancer Detection Techniques Using Machine Learning
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