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| Brain Age Prediction Methods and Applications Based on Multimodal Neuroimaging Data |
| Liu Shuang1,2, Yu Jing1, Chen Yuanyuan1,2,*, Fan Qiuyun2,3, Zhao Xin1,2, Ming Dong1,2,3# |
1(Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China);
2(Tianjin Center for Brain Science,Tianjin 300072,China);
3(College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China |
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Abstract Brain age can predict the degree of brain maturity and aging by modeling and analysis of neuroimaging data. With the development of artificial intelligence algorithms, the related research on brain age prediction have demonstrated a rapid emerging trend. It is generally recognized that brain age can be an effective biomarker for monitoring abnormal development and aging, which can assess individual brain health, and has great potential to detect abnormal aging and disease. In the context of rapid growing of research interests on the brain age prediction, this review summarized the latest achievements from the aspects of brain age classification, brain age model, clinical application, and further discusses challenges and developing directions of brain age in the future studies.
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Received: 02 September 2022
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