TY  - GEN
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.
DO  - 10.6083/bpxhc43431
DO  - doi
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
T1  - Deep learning and structural MRI: in pursuit of improved prediction of self-regulatory behavior and mental health
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
DA  - 2022-02-01
AU  - Harman, Gareth
L1  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
PB  - Oregon Health and Science University
LA  - eng
PY  - 2022-02-01
ID  - 43431
L4  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
KW  - Neuroimaging
KW  - Deep Learning
KW  - Mental Health
KW  - Artificial Intelligence
KW  - Magnetic Resonance Imaging
TI  - Deep learning and structural MRI: in pursuit of improved prediction of self-regulatory behavior and mental health
Y1  - 2022-02-01
L2  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
LK  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
UR  - https://digitalcollections.ohsu.edu/record/43431/files/Harman.Gareth.2024.pdf
ER  -