TY  - GEN
AB  - Nearly one in five children (17%) aged 2-8 were diagnosed with either a mental, emotional, developmental, or behavioral disorder in 2016 in the US. Early identification of MHD is crucial, as many mental health conditions first appear during these formative years, offering a unique window for effective intervention and improving healthy transition into adulthood. This dissertation evaluates the use of novel modeling strategies, namely artificial intelligence (deep learning), and their application to structural neuroimaging data (MRI) in predicting self-regulatory behavior and mental health.
AD  - Oregon Health and Science University
AU  - Harman, Gareth
DA  - 2022-02-01
DO  - 10.6083/bpxhc43431
DO  - doi
ED  - Kalpathy-Cramer, Jayashree
ED  - Nagel, Bonnie
ED  - Mooney, Michael
ED  - Morales, Angelica
ED  - Dufford, Alexander
ED  - Evans, Nathaniel
ED  - Committee member
ED  - Committee chair
ED  - Academic advisor
ED  - Committee member
ED  - Committee member
ED  - Collaborator
ID  - 43431
KW  - Neuroimaging
KW  - Deep Learning
KW  - Mental Health
KW  - Artificial Intelligence
KW  - Magnetic Resonance Imaging
L1  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
L2  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
L4  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
LA  - eng
LK  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
N2  - Nearly one in five children (17%) aged 2-8 were diagnosed with either a mental, emotional, developmental, or behavioral disorder in 2016 in the US. Early identification of MHD is crucial, as many mental health conditions first appear during these formative years, offering a unique window for effective intervention and improving healthy transition into adulthood. This dissertation evaluates the use of novel modeling strategies, namely artificial intelligence (deep learning), and their application to structural neuroimaging data (MRI) in predicting self-regulatory behavior and mental health.
PB  - Oregon Health and Science University
PY  - 2022-02-01
T1  - Deep learning and structural MRI: in pursuit of improved prediction of self-regulatory behavior and mental health
TI  - Deep learning and structural MRI: in pursuit of improved prediction of self-regulatory behavior and mental health
UR  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
Y1  - 2022-02-01
ER  -