Artificial Neural Networks for Early Diagnosis of Alzheimer’s Disease
Published in In Progress, 2026
This ongoing research project, conducted under the supervision of Professor Qihong Lu at the Department of Neuroscience, City University of Hong Kong, aims to develop machine learning models for early Alzheimer’s disease diagnosis. The project leverages artificial neural networks to identify subtle patterns in neuroimaging and behavioral data that may indicate early-stage neurodegeneration.
Research Objectives
- Develop deep learning architectures for analyzing neuroimaging datasets
- Identify computational biomarkers for early AD detection
- Compare ANN performance with traditional diagnostic methods
- Investigate the relationship between computational models and biological mechanisms of memory formation
Current Status
Data collection and model development phase
Expected Outcomes
Conference presentation and manuscript submission planned for 2026-2027
Recommended citation: Lu, Qihong*, & CHENG, Wan Kiu Winkey. (2026). "Artificial Neural Networks for Early Diagnosis of Alzheimer Disease." In Progress.
Download Paper