Technical Name 以統合分析與機器學習技術建構集成式大腦生物年齡估算平台
Project Operator National Yang Ming Chiao Tung University
Project Host 林慶波
Based on our long-term accumulated healthy brain image database, we used meta-analysismultivariate analytical algorithms to extract the cognitive biological characteristics of individual subjects. By using machine learning / artificial intelligence algorithms, these features were further calculated for capturing individual cognition according to related brain networks. This biological index could be a potential marker for evaluating individual brain health, cognitive functions,risk for neurodegenerative diseases.
Technical Film
Scientific Breakthrough
First, a unique multi-site neuroimaging database was constructed from Taiwan health residentsits constructed prediction models can be promoted to apply for Asia populations. Second, we obtain different cognitive function features from a huge multi-site neuroimaging dataset with optimized neuroimaging preprocess including meta-multivariate analysis. Finally, we provide an ensemble learning framework with machine learning algorithms to evaluate individual brain health in cognitive function.
Industrial Applicability
This technique aims to provide an objective biological quantitative index to evaluate individual brain healthto assess the change of cognitive-related behavior during aging. This brain aging biomarker can be used in clinical diseases, including neurodegenerative diseases, neuropsychiatric diseases,geriatrics. Moreover, this individual health prediction framework also can be potential to apply in fields of cognition training intervention, personal health risk evaluation, preventive medicine,even insurance.
Matching Needs
Keyword Aging Brain network Brain image Cognition Meta-analysis Machine learning Artificial intelligence Health Brain age
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