An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images
Summary
An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images is a scholarly article[1].
Key Facts
An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-efficientnet-integrated-resnet-deep-network-and-explainable-ai-for-breast-lesion-classification-from-ultrasound-image
MLA“An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-efficientnet-integrated-resnet-deep-network-and-explainable-ai-for-breast-lesion-classification-from-ultrasound-image.
BibTeX@misc{4ortxyz_an-efficientnet-integrated-resnet-deep-network-and-explainable-ai-for-breast-lesion-classification-from-ultrasound-image_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images}}, year = {2026}, url = {https://4ort.xyz/entity/an-efficientnet-integrated-resnet-deep-network-and-explainable-ai-for-breast-lesion-classification-from-ultrasound-image}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images — https://4ort.xyz/entity/an-efficientnet-integrated-resnet-deep-network-and-explainable-ai-for-breast-lesion-classification-from-ultrasound-image (retrieved 2026-05-24)