Using NACC data (n=52,537), we built a lightweight, interpretable ML model for Alzheimer’s prediction.
Our 19-feature LightGBM hit ROC-AUC 0.90 with strong clinical value.
Link: alz-journals.onlinelibrary.wiley.com/doi/10.1002/...
Using NACC data (n=52,537), we built a lightweight, interpretable ML model for Alzheimer’s prediction.
Our 19-feature LightGBM hit ROC-AUC 0.90 with strong clinical value.
Link: alz-journals.onlinelibrary.wiley.com/doi/10.1002/...
We developed a lightweight, interpretable ML tool for Alzheimer’s prediction using NACC data (n=52,537).
A 19-feature LightGBM model reached ROC-AUC 0.90 with strong clinical applicability.
Link: dx.doi.org/10.1002/dad2...
We developed a lightweight, interpretable ML tool for Alzheimer’s prediction using NACC data (n=52,537).
A 19-feature LightGBM model reached ROC-AUC 0.90 with strong clinical applicability.
Link: dx.doi.org/10.1002/dad2...
Voting closes JUNE 25!!!
alz.surveymonkey.com/r/T8GC8J6
Voting closes JUNE 25!!!
alz.surveymonkey.com/r/T8GC8J6
Grateful to the @alzassociation.bsky.social for this opportunity to represent and advocate for global Alzheimer’s research and collaboration.
Excited to connect and contribute at #AAIC2025 — see you there!
Meet them at alz.org/ISTAARTambassadors
@alzassociation.bsky.social
Grateful to the @alzassociation.bsky.social for this opportunity to represent and advocate for global Alzheimer’s research and collaboration.
Excited to connect and contribute at #AAIC2025 — see you there!