Development of AI‐4‐AD tools for evaluation and prognosis of AD conversion: multi‐branch network and multi‐task deep learning algorism
Our DL method consolidates multi-modal medical information at different visits to predict the disease's progression, which greatly improved AD prognosis from those using traditional DL algorithms (CNN, LeNet and ResNet). The AI4AD framework proposed here can also be tailored to other diseases with similar data characteristics.
Authors
- Ran Pang (ORCID: https://orcid.org/0000-0001-7978-7325)
- Liang Han (ORCID: https://orcid.org/0000-0002-9235-7319)
- Qing Yang (ORCID: https://orcid.org/0000-0003-1170-3978)
- Yuan Liu (ORCID: https://orcid.org/0000-0003-4887-907X)
- Y. X. Tan (ORCID: https://orcid.org/0000-0002-9906-7875)
- Xiujuan Pu
- Qing Ren
Institutions
- Pennsylvania State University (US)
- Chongqing University (CN)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/alz.092964
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00