Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis

Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis

ABSTRACT Background The demand for fresh strategies to analyze intricate multidimensional data in neuroscience is increasingly evident. One of the most complex events during our neurodevelopment is adolescence, where our nervous system suffers constant changes, not only in neuroanatomical traits but...

Full description

Saved in:
Bibliographic Details
Main Authors: Marcos Uceta, Alberto del Cerro‐León, Danylyna Shpakivska‐Bilán, Luis M. García‐Moreno, Fernando Maestú, Luis Fernando Antón‐Toro
Format: Article
Language:English
Published: Wiley 2024-11-01
Series:Brain and Behavior
Subjects:
binge drinking
clustering
electrophysiology
predisposition factors
unsupervised machine learning
Online Access:https://doi.org/10.1002/brb3.70157
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1002/brb3.70157

Similar Items