Machine learning-based classification of chronic traumatic brain injury using hybrid diffusion imaging.

ABSTRACT:

Background and purpose

Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging.

Materials and methods

A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging (HYDI) data and then used supervised learning algorithms to classify t

SUBMITTER: Muller JJ 

PROVIDER: S-EPMC10484001 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature