Type 2 diabetes data classification using stacked autoencoders in deep neural networks

Research article (Clinical Epidemiology and Global Health, 2018) · cited 172× · AI/ML

CreativeWork academia openalex:W2905097366

Press Enter · cited answer in seconds

Summary

Type 2 diabetes data classification using stacked autoencoders in deep neural networks is a scholarly article^[1].

Key Facts

Type 2 diabetes data classification using stacked autoencoders in deep neural networks's instance of is recorded as scholarly article^[2].

📜 Data licence

Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex

⭐ Popularity Graph

0/100 long tail

Quick Facts

Instance of scholarly article

Publication date December 10, 2018

Properties

Published in Clinical epidemiology and global health

Title lang: en, text: Type 2 diabetes data classification using stacked autoencoders in deep neural networks

External References (2)

Doi 10.1016/J.CEGH.2018.12.004

Openalex id W2905097366

🔗 Connections

Authored by 3

Damodar Reddy Edla, K Kannadasan, Venkatanareshbabu Kuppili

← Author of 3

Damodar Reddy Edla, K Kannadasan, Venkatanareshbabu Kuppili

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

[2] ↑ Type 2 diabetes data classification using stacked autoencoders in deep neural networks — instance of (P31): scholarly article. wikidata.org.

Class ancestry

[1] ↑ Type 2 diabetes data classification using stacked autoencoders in deep neural networks is an instance of scholarly article (scholarly article) [P31, primary]. Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA

4ort.xyz Knowledge Graph. (2026). Type 2 diabetes data classification using stacked autoencoders in deep neural networks. Retrieved October 18, 2026, from https://4ort.xyz/entity/type-2-diabetes-data-classification-using-stacked-autoencoders-in-deep-neural-networks

MLA

“Type 2 diabetes data classification using stacked autoencoders in deep neural networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 18 Oct. 2026, https://4ort.xyz/entity/type-2-diabetes-data-classification-using-stacked-autoencoders-in-deep-neural-networks.

BibTeX

@misc{4ortxyz_type-2-diabetes-data-classification-using-stacked-autoencoders-in-deep-neural-networks_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Type 2 diabetes data classification using stacked autoencoders in deep neural networks}}, year = {2026}, url = {https://4ort.xyz/entity/type-2-diabetes-data-classification-using-stacked-autoencoders-in-deep-neural-networks}, note = {Accessed: 2026-10-18}}

LLM prompt

According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Type 2 diabetes data classification using stacked autoencoders in deep neural networks — https://4ort.xyz/entity/type-2-diabetes-data-classification-using-stacked-autoencoders-in-deep-neural-networks (retrieved 2026-10-18)

Canonical URL: https://4ort.xyz/entity/type-2-diabetes-data-classification-using-stacked-autoencoders-in-deep-neural-networks · Last refreshed: October 18, 2026