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Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation

https://doi.org/10.2196/18563
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1 of 62 checkable references need attention · checked 2026-08-25

At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.

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no DOI — not checkedRuderSAn overview of gradient descent optimization algorithmsarXiv20172020-11-18https://arxiv.org/abs/1609.04747
no DOI — not checkedDongguk University2020-11-18http://dm.dgu.edu/link.html
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no DOI — not checkedDeep learning toolboxMathworks2020-11-18https://in.mathworks.com/products/deeplearning.html
no DOI — not checkedGastrolab - the gastrointestinal siteGastrolab2020-11-18http://www.gastrolab.net/ni.htm
no DOI — not checkedIntel Core i7-3770K ProcessorIntel2020-11-18https://ark.intel.com/content/www/us/en/ark/products/65523/intel-core-i7-3770k-processor-8m-cache-up-to-3-90-ghz.html
no DOI — not checkedGeForce GTX 1070GeForce2020-11-18https://www.geforce.com/hardware/desktop-gpus/geforce-gtx-1070/specifications
no DOI — not checkedSimonyanKZissermanAVery deep convolutional networks for large-scale image recognition20153rd International Conference on Learning RepresentationsMay 7-9, 2015San Diego, CA
no DOI — not checkedIandolaFHanSMoskewiczMAshrafKDallyWKeutzerKarXiv2020-11-18https://arxiv.org/abs/1602.07360
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