Predicting cognitive decline: Deep-learning reveals subtle brain changes in pre-MCI stage
This study effectively predicted the progression to MCI among order individuals at normal cognition state by deep learning algorithm with MRI scans. Exploring the key brain alterations during the very early stages, specifically the transition from NC to MCI, based on deep learning methods holds significant potential for further research and contributes to a deeper understanding of disease mechanisms.
Authors
- Dinggang G. Shen (ORCID: https://orcid.org/0000-0002-7934-5698)
- Yongsheng Pan (ORCID: https://orcid.org/0000-0002-8067-1132)
- Zhen Gu (ORCID: https://orcid.org/0000-0003-2947-4456)
- Mingxia Liu (ORCID: https://orcid.org/0000-0002-0166-0807)
- Ling Yue (ORCID: https://orcid.org/0000-0001-6476-0189)
- Shifu Xiao (ORCID: https://orcid.org/0000-0002-4721-9646)
- Wei Li (ORCID: https://orcid.org/0000-0002-1025-3664)
- J. R. Mao (ORCID: https://orcid.org/0009-0005-1400-5501)
- Bo Hong
Institutions
- University of North Carolina at Chapel Hill (US)
- Northwestern Polytechnical University (CN)
- Shanghai Mental Health Center (CN)
- ShanghaiTech University (CN)
Publication Details
- Journal
- The Journal of Prevention of Alzheimer s Disease
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1016/j.tjpad.2025.100079
- Citations
- 10
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 14.71
Funders
- National Natural Science Foundation of China
- Ministry of Science and Technology of the People's Republic of China
- Shanghai Municipal Health Bureau
- ShanghaiTech University
- Shanghai Clinical Research Center for Mental Health
- Postdoctoral Research Foundation of China