Depression and anxiety disorders are two of the most diagnosed mental disorders in adolescents. These disorders can be debilitating and put significant burdens on the quality of life of the children and parents. Pathological changes in the brain’s structural anatomy have been investigated using Magnetic resonance imaging (MRI). Statistical analysis, machine learning, and deep learning techniques have identified key regions of interest in the brain whose abnormalities are associated with these disorders. The Adolescent Brain Cognitive Development (ABCD) study is the largest longitudinal study of childhood brain development in the United States. Using data provided by ABCD, this study aims to differentiate between anxiety and depression diagnoses and identify key regions of interest in the brain using a 3D Convolutional Neural Network and Random Forest analysis.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Kongsomjit, Pitipat
• Deckers, Olivia

Publisher

• Worcester Polytechnic Institute

Identifier

• 119169
• E-project-032224-150711

Advisor

• Nephew, Benjamin
• Korkin, Dmitry
• Rodriguez, Angela C Incollingo

Year

• 2024

Date created

• 2024-03-22

Resource type

• Major Qualifying Project

Major

• Data Science
• Bioinformatics & Computational Biology

Source

• E-project-032224-150711

Rights statement

• In Copyright