Advancing Predictive Models for Early Detection of Alzheimer's Disease: Integrating Speech Characteristics and Cardiovascular Risk Factors for Enhanced ATN Biomarker Status Prediction
Incorporating cardiovascular and speech features significantly improved model performance for predicting ATN pathology. These findings underscore the potential for non-invasive, scalable tools to detect early AD-related changes, reducing dependence on invasive diagnostic tests.
Authors
- Ivan Koychev (ORCID: https://orcid.org/0000-0001-6813-8493)
- Harshita Sinha (ORCID: https://orcid.org/0000-0001-7489-2425)
- Ishan Durve (ORCID: https://orcid.org/0009-0000-2522-3663)
- N Tahira
- Dishaa Sinha
- Kushagra Soni
- Iman Kashif
- Junaid Chaudhary
- Vaibhav Soni
- Hussein Mehmet
Institutions
- Fergusson College (IN)
- Nottinghamshire Healthcare NHS Foundation Trust (GB)
- Cambridge University Hospitals NHS Foundation Trust (GB)
- University of Oxford (GB)
- Defence Avionics Research Establishment (IN)
- West London Mental Health NHS Trust (GB)
- Imperial College London (GB)
- University of Sheffield (GB)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_103534
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00