Work

Data-driven spatiotemporal modeling reveals personalized trajectories of cortical atrophy in Alzheimer's disease.

Year: 2025

Type: preprint

Abstract: , tau, neurodegeneration, and cognition-outperforming clinical and neuroimaging benchmarks. Patient-specific parameters reveal distinct progression subtypes and anticipate future cognitive decline more effectively than standard biomarkers. Sensitivity analysis highlights regional drivers of disease spread, reproducing known temporolimbic and frontal vulnerability patterns. This network-based digital-twin framework offers a quantitative, personalized paradigm for AD trajectory prediction, with implications for patient stratification, clinical trial design, and targeted therapeutic development.

Source: PubMed

Authors: Chunyan Li, Yutong Mao, Xiao Liu, Wenrui Hao

Institution: Pennsylvania State University

Language: English

Topic: Dementia and Cognitive Impairment Research

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of General Medical Sciences

Awards: A pathophysiology driven spatial dynamic modeling framework for personalized prediction and precision medicine, G4970906380

OpenAlex ID: W4416223230

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