BiomarkersIn silico
Machine Learning Approach for Predicting Amyloid and Tau Positivity in Alzheimer's Disease Using Clinically Accessible Features
AAIC 2025 Abstract
Abstract
Background: Prediction of Alzheimer's disease (AD) biomarkers can improve public health strategies, especially if achieved with easily collectable data in a single consultation. Machine learning (ML) offers versatile tools for clinical and research applications.
The paper
Daniel Arnold, Luiza Santos Machado, Nesrine Rahmouni, Alzheimer's Disease Neuroimaging Initiative
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Joseph Therriault, Stijn Servaes, Jenna Stevenson, Arthur C. Macedo, Artur Francisco Schumacher‐Schuh, Christian Mattjie, Firoza Zubeida Lussier, Mira Chamoun, Gleb Bezgin, Andrea Lessa Benedet, Tharick Ali Pascoal, Rodrigo C. Barros, Marco Antônio De Bastiani, Pedro Rosa‐Neto, Eduardo Rigon Zimmer, Wyllians Vendramini Borelli,Universidade Federal do Rio Grande do Sul · University of Southern California
AAIC 2025 Abstract · 8 Jan 2026 · CC BY
Presented at AAIC 2025
