Development of an individualized dementia risk prediction model using deep learning survival analysis incorporating genetic and environmental factors
This study successfully developed and validated the DeepSurv dementia prediction model for individuals aged 60 years and above, integrating both genetic and clinical data. The model was then deployed on AliCloud servers to promote its clinical translation. It is anticipated that this prediction model will provide more accurate decision support for clinical treatment and will serve as a valuable tool for the primary prevention of dementia.
Authors
- Shiqi Yuan (ORCID: https://orcid.org/0000-0002-2794-2546)
- Jie Yang (ORCID: https://orcid.org/0000-0003-3469-5931)
- Shanyuan Tan
- Qingqing Ye (ORCID: https://orcid.org/0009-0009-1023-535X)
- Xiaoxue Peng (ORCID: https://orcid.org/0000-0001-8687-9711)
- Jun Lyu (ORCID: https://orcid.org/0000-0002-2237-8771)
- Xiaxuan Huang (ORCID: https://orcid.org/0000-0001-6248-2891)
- Yitong Ling
- Qing Liu (ORCID: https://orcid.org/0000-0001-5286-4423)
- Juan Yu (ORCID: https://orcid.org/0000-0002-2723-3539)
- Lei Feng (ORCID: https://orcid.org/0009-0009-0129-2977)
- Zihong Bai
- Huan Le
Institutions
- Guiyang Medical University (CN)
- Guangdong Provincial Hospital of Traditional Chinese Medicine (CN)
- First Affiliated Hospital of Jinan University (CN)
Publication Details
- Journal
- Alzheimer s Research & Therapy
- Published
- 2024-12-30
- DOI
- https://doi.org/10.1186/s13195-024-01663-w
- Citations
- 5
- Primary Topic
- Health, Environment, Cognitive Aging
- Type
- article
- Field-Weighted Citation Impact
- 1.57