Predicting suicidality in late‐life depression by 3D convolutional neural network and cross‐sample entropy analysis of resting‐state fMRI

Predicting suicidality in late‐life depression by 3D convolutional neural network and cross‐sample entropy analysis of resting‐state fMRI

Abstract Background: Predicting suicide is a pressing issue among older adults; however, predicting its risk is difficult. Capitalizing on the recent development of machine learning, considerable progress has been made in predicting complex behavior such as suicide. As depression remained the strong...

Full description

Bibliographic Details
Main Authors: Chemin Lin, Chih‐Mao Huang, Wei Chang, You‐Xun Chang, Ho‐Ling Liu, Shu‐Hang Ng, Huang‐Li Lin, Tatia Mei‐Chun Lee, Shwu‐Hua Lee, Shun‐Chi Wu
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Brain and Behavior
Subjects:
convolutional neural network
cross‐sample entropy
machine learning
older adult
resting‐state fMRI
suicide
Online Access:https://doi.org/10.1002/brb3.3348

Internet

https://doi.org/10.1002/brb3.3348

Similar Items