Deep learning detection of informative features in tau PET for Alzheimer’s disease classification
Abstract
Alzheimer’s disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and there is currently no approved disease-modifying treatment. Biomarkers for early detection and mechanistic understanding of disease course are critical for drug development and clinical trials. Amyloid has been the focus of most biomarker research. Here, we developed a deep learning-based framework to identify informative features for AD classification using tau positron emission tomography (PET) scans.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 01, 2020
- Source ID
- 10.1186/s12859-020-03848-0
Entities
People
- Andrew J. Saykin
- For The Alzheimer’s Neuroimaging Initiative
- Kwangsik Nho
- Shannon L. Risacher
- Taeho Jo
Organizations
- National Cancer Institute
- National Institute on Aging
- United States Department of Defense
- United States National Library of Medicine