Classification and Interpretability of Mild Cognitive Impairment Based on Resting-State Functional Magnetic Resonance and Ensemble Learning

The combination and integration of multimodal imaging and clinical markers have introduced numerous classifiers to improve diagnostic accuracy in detecting and predicting AD; however, many studies cannot ensure the homogeneity of data sets and consistency of results. In our study, the XGBoost algori...

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Detalles Bibliográficos
Autores principales: Hu, Mengjie, Yu, Yang, He, Fangping, Su, Yujie, Zhang, Kan, Liu, Xiaoyan, Liu, Ping, Liu, Ying, Peng, Guoping, Luo, Benyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417789/
https://www.ncbi.nlm.nih.gov/pubmed/36035823
http://dx.doi.org/10.1155/2022/2535954

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417789/
https://www.ncbi.nlm.nih.gov/pubmed/36035823
http://dx.doi.org/10.1155/2022/2535954

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