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End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma

Research article (Quantitative Imaging in Medicine and Surgery, 2023) · cited 11× · AI/ML
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End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma

Summary

End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma is a scholarly article[1].

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  • End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma. Retrieved May 24, 2026, from https://4ort.xyz/entity/end-to-end-deep-learning-radiomics-development-and-validation-of-a-novel-attention-based-aggregate-convolutional-neural-
MLA “End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/end-to-end-deep-learning-radiomics-development-and-validation-of-a-novel-attention-based-aggregate-convolutional-neural-.
BibTeX @misc{4ortxyz_end-to-end-deep-learning-radiomics-development-and-validation-of-a-novel-attention-based-aggregate-convolutional-neural-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma}}, year = {2026}, url = {https://4ort.xyz/entity/end-to-end-deep-learning-radiomics-development-and-validation-of-a-novel-attention-based-aggregate-convolutional-neural-}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma — https://4ort.xyz/entity/end-to-end-deep-learning-radiomics-development-and-validation-of-a-novel-attention-based-aggregate-convolutional-neural- (retrieved 2026-05-24)

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