Deep Multimodal Learning From MRI and Clinical Data for Early Prediction of Neurodevelopmental Deficits in Very Preterm Infants.
He, L; Li, H; Chen, M; Wang, J; Altaye, M; Dillman, JR; Parikh, NA.
Frontiers in Neuroscience.
2021;
15.
Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants.
Chandwani, R; Kline, JE; Harpster, K; Tkach, J; Parikh, NA; Altaye, M; Arnsperger, A; Beiersdorfer, T; Bridgewater, K; Cahill, T; et al.
Human Brain Mapping.
2021;
42:4708-4721.
Effects of prenatal opioid exposure on functional networks in infancy.
Merhar, SL; Jiang, W; Parikh, NA; Yin, W; Zhou, Z; Tkach, JA; Wang, L; Kline-Fath, BM; He, L; Braimah, A; et al.
Developmental Cognitive Neuroscience.
2021;
51.
Prenatal opioid exposure is associated with smaller brain volumes in multiple regions.
Merhar, SL; Kline, JE; Braimah, A; Kline-Fath, BM; Tkach, JA; Altaye, M; He, L; Parikh, NA.
Pediatric Research.
2021;
90:397-402.
Diffusion MRI Microstructural Abnormalities at Term-Equivalent Age Are Associated with Neurodevelopmental Outcomes at 3 Years of Age in Very Preterm Infants.
Parikh, MN; Chen, M; Braimah, A; Kline, J; McNally, K; Logan, JW; Tamm, L; Yeates, KO; Yuan, W; He, L; et al.
American Journal of Neuroradiology.
2021;
42:1535-1542.
Diffuse white matter abnormality in very preterm infants at term reflects reduced brain network efficiency.
Kline, JE; Illapani, VS P; Li, H; He, L; Yuan, W; Parikh, NA.
NeuroImage: Clinical.
2021;
31.
Perinatal Risk and Protective Factors in the Development of Diffuse White Matter Abnormality on Term-Equivalent Age Magnetic Resonance Imaging in Infants Born Very Preterm.
Parikh, NA; Sharma, P; He, L; Li, H; Altaye, M; Priyanka Illapani, VS; Arnsperger, A; Beiersdorfer, T; Bridgewater, K; Cahill, T; et al.
Journal of Pediatrics.
2021;
233:58-65.e3.
Automatic Segmentation of Diffuse White Matter Abnormality on T2-weighted Brain MR Images Using Deep Learning in Very Preterm Infants.
Li, H; Chen, M; Wang, J; Illapani, VS P; Parikh, NA; He, L.
Radiology. Artificial intelligence..
2021;
3.
Current and emerging artificial intelligence applications for pediatric abdominal imaging.
Dillman, JR; Somasundaram, E; Brady, SL; He, L.
Pediatric Radiology.
2021.
DeepLiverNet: a deep transfer learning model for classifying liver stiffness using clinical and T2-weighted magnetic resonance imaging data in children and young adults.
Li, H; He, L; Dudley, JA; Maloney, TC; Somasundaram, E; Brady, SL; Parikh, NA; Dillman, JR.
Pediatric Radiology.
2021;
51:392-402.