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Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases

Abstract Accurate and scalable quantification of amyloid-β (Aβ) pathology is crucial for deeper disease phenotyping and furthering research in Alzheimer Disease (AD). This multidisciplinary study addresses the current limitations on neuropathology by leveraging a machine learning (ML) pipeline to pe...

Whakaahuatanga katoa

I tiakina i:
Ngā kaituhi matua: Rebeca Scalco, Luca C. Oliveira, Zhengfeng Lai, Danielle J. Harvey, Lana Abujamil, Charles DeCarli, Lee-Way Jin, Chen-Nee Chuah, Brittany N. Dugger
Hōputu: Artigo
Reo:Inglês
I whakaputaina: BMC 2024-08-01
Rangatū:Acta Neuropathologica Communications
Ngā marau:
Machine learning
Quantitative analysis
Neuropathology
Whole-slide imaging
Clinicopathological correlation
Urunga tuihono:https://doi.org/10.1186/s40478-024-01827-7
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