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Kyunglok Baik

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Articles

Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals

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By Ioanna Skampardoni, Guray Erus, Ilya M. Nasrallah, Zhijian Yang, Michael Duggan, Keenan A. Walker, Alexander Getka, Kyunglok Baik, Randa Melhem, Sindhuja T Govindarajan, Susan M. Resnick, Haochang Shou, Konstantina Nikita, Christos Davatzikos
| Flipboard
Some students get tutoring but end up as ‘intervention lifers.’ This common sense tactic could help. Knox County Schools looked like it was doing …
Open in Who Shared Issue with article?

Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals

|
By Ioanna Skampardoni, Guray Erus, Ilya M. Nasrallah, Zhijian Yang, Michael Duggan, Keenan A. Walker, Alexander Getka, Sindhuja T Govindarajan, Susan M. Resnick, Haochang Shou, Christos Davatzikos, Kyunglok Baik, Randa Melhem, Konstantina Nikita
| Nature Verified
Abstract Machine learning can unravel heterogeneous patterns of brain aging and neurodegeneration, but existing methods offer limited insights into disease progression due to reliance on cross-sectional data. We introduce Coupled Cross-sectional and Longitudinal Non-negative Matrix Factorization (CCL-NMF) to capture dominant brain aging patterns by simultaneously leveraging cross-sectional and longitudinal neuroimaging data.
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