A CNN-Based Autoencoder and Machine Learning Model for Identifying Betel-Quid Chewers Using Functional MRI Features

Betel quid (BQ) is one of the most commonly used psychoactive substances in some parts of Asia and the Pacific. Although some studies have shown brain function alterations in BQ chewers, it is virtually impossible for radiologists’ to visually distinguish MRI maps of BQ chewers from others. In this...

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Detalles Bibliográficos
Autores principales: Ho, Ming-Chou, Shen, Hsin-An, Chang, Yi-Peng Eve, Weng, Jun-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234239/
https://www.ncbi.nlm.nih.gov/pubmed/34207169
http://dx.doi.org/10.3390/brainsci11060809

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234239/
https://www.ncbi.nlm.nih.gov/pubmed/34207169
http://dx.doi.org/10.3390/brainsci11060809

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