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Unsupervised machine learning integrates genomic variants and EMR to unravel mechanisms of brain hemorrhage and epilepsy as early indicators of Alzheimer’s in Down Syndrome

Crossref DOI link: https://doi.org/10.1186/s13195-025-01946-w

Published Online: 2025-12-19

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Liu, Yichuan

Qu, Hui-Qi

Chang, Xiao

Mentch, Frank D.

Qiu, Haijun

Nguyen, Kenny

Eister, Garnet

Ostberg, Kayleigh

Glessner, Joseph

Hakonarson, Hakon
Funding

Funding for this research was provided by:

Children's Hospital of Philadelphia
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Text and Data Mining valid from 2025-12-19

Version of Record valid from 2026-01-28
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Article History

Received: 29 July 2025

Accepted: 17 December 2025

First Online: 19 December 2025

Declarations

:

: We confirm that all methods were carried out in accordance with relevant regulatory guidelines and regulations. All experimental protocols were approved by the Institutional Review Board (IRB) of the Children’s Hospital of Philadelphia (CHOP) with the IRB number: IRB 16-013278. Informed consent was obtained from all subjects. If subjects are under 18, consent was obtained from a parent and/or legal guardian with assent from the child if 7 years or older.

: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

: The authors declare no competing interests.

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