Home ›
Entities
› academia
› Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation
Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation
Research article (Alzheimer s & Dementia Translational Research & Clinical Interventions, 2019) · cited 118× · AI/ML
Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation is a scholarly article[1].
Key Facts
Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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.
APA4ort.xyz Knowledge Graph. (2026). Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation. Retrieved October 19, 2026, from https://4ort.xyz/entity/convolution-neural-networkbased-alzheimer-s-disease-classification-using-hybrid-enhanced-independent-component-analysis-
MLA“Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 19 Oct. 2026, https://4ort.xyz/entity/convolution-neural-networkbased-alzheimer-s-disease-classification-using-hybrid-enhanced-independent-component-analysis-.
BibTeX@misc{4ortxyz_convolution-neural-networkbased-alzheimer-s-disease-classification-using-hybrid-enhanced-independent-component-analysis-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation}}, year = {2026}, url = {https://4ort.xyz/entity/convolution-neural-networkbased-alzheimer-s-disease-classification-using-hybrid-enhanced-independent-component-analysis-}, note = {Accessed: 2026-10-19}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation — https://4ort.xyz/entity/convolution-neural-networkbased-alzheimer-s-disease-classification-using-hybrid-enhanced-independent-component-analysis- (retrieved 2026-10-19)
