| Title: | Age-level bias correction in brain age prediction |
| Journal: | NeuroImage Clinical |
| Published: | 7 Jan 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36634514/ |
| DOI: | https://doi.org/10.1016/j.nicl.2023.103319 |
Publication 7997
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
The predicted age difference (PAD) between an individual's predicted brain age and chronological age has been commonly viewed as a meaningful phenotype relating to aging and brain diseases. However, the systematic bias appears in the PAD achieved using machine learning methods. Recent studies have designed diverse bias correction methods to eliminate it for further downstream studies. Strikingly, here we demonstrate that bias still exists in the PAD of samples with the same age even after kind of correction. Therefore, current PAD may not be taken as a reliable phenotype and more investigations are needed to solve this fundamental defect. To this end, we propose an age-level bias correction method and demonstrate its efficacy in numerical experiments.4 Authors
- Biao Zhang
- Shuqin Zhang
- Jianfeng Feng
- Shihua Zhang
1 Application
| Application ID | Title |
|---|---|
| 19542 | Identifying multi-level biomarkers and disease mechanisms for major mental disorders |
Enabling scientific discoveries that improve human health