BrainNetScore: Enhancing Alzheimer’s disease risk prediction using genetic‐guided brain volumetric phenotype network

BrainNetScore significantly improves AD risk prediction when combined with PRSs. This highlights the potential of network-based approaches and comprehensive genetic analysis in developing personalized medicine strategies for AD. Future work should extend this model to diverse populations.

Authors

Institutions

Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.084351
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BrainNetScore: Enhancing Alzheimer’s disease risk prediction using genetic‐guided brain volumetric phenotype network

Sang‐Hyuk Jung, Jakob Woerner, Yonghyun Nam, Haochang Shou et al.
Alzheimer s & Dementia
Brain Tumor Detection and Classification
article

BrainNetScore: Enhancing Alzheimer’s disease risk prediction using genetic‐guided brain volumetric phenotype network

Sang‐Hyuk Jung, Jakob Woerner, Yonghyun Nam, Haochang Shou, Erica H Suh, Dokyoon Kim, Li Shen
article en

Abstract

BrainNetScore significantly improves AD risk prediction when combined with PRSs. This highlights the potential of network-based approaches and comprehensive genetic analysis in developing personalized medicine strategies for AD. Future work should extend this model to diverse populations.

Alzheimer s & DementiaVol. 20(S1)
University of Pennsylvania (US)
Openalex Percentile: Top 72%
Brain Tumor Detection and Classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.