Nehal A. Parikh

According to our database, Nehal A. Parikh authored at least 12 papers between 2013 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

RadCLIP: Enhancing Radiologic Image Analysis Through Contrastive Language-Image Pretraining.

Zhixiu Lu, Hailong Li, Nehal A. Parikh, Jonathan R. Dillman, Lili He

IEEE Trans. Neural Networks Learn. Syst., October, 2025

Altered neurobehavioral white matter integrity in preterm children: A confounding-controlled analysis using the adolescent brain and cognitive development (ABCD) study.

Hailong Li, Yuwen Hung, Junqi Wang, Nicole Rudberg, Nehal A. Parikh, Lili He

NeuroImage, 2025

Development and Validation of a Modality-Invariant 3D Swin U-Net Transformer for Liver and Spleen Segmentation on Multi-Site Clinical Bi-parametric MR Images.

Huixian Zhang, Hailong Li, Redha Ali, Wei Jia, Wen Pan, Scott B. Reeder, David Harris, William R. Masch, Anum Aslam, Krishna Shanbhogue, Nehal A. Parikh, Jonathan R. Dillman, Lili He

J. Imaging Inform. Medicine, 2025

2024

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Hailong Li, Junqi Wang, Zhiyuan Li, Kim M. Cecil, Mekibib Altaye, Jonathan R. Dillman, Nehal A. Parikh, Lili He

NeuroImage, 2024

DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants.

Junqi Wang, Hailong Li, Kim M. Cecil, Mekibib Altaye, Nehal A. Parikh, Lili He

Comput. Methods Programs Biomed., 2024

Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment.

Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Mekibib Altaye, Kim M. Cecil, Nehal A. Parikh, Lili He

Artif. Intell. Medicine, 2024

2023

A novel collaborative self-supervised learning method for radiomic data.

Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Nehal A. Parikh, Lili He

NeuroImage, August, 2023

Dynamic weighted hypergraph convolutional network for brain functional connectome analysis.

Junqi Wang, Hailong Li, Gang Qu, Kim M. Cecil, Jonathan R. Dillman, Nehal A. Parikh, Lili He

Medical Image Anal., 2023

2022

A novel Ontology-guided Attribute Partitioning ensemble learning model for early prediction of cognitive deficits using quantitative Structural MRI in very preterm infants.

Zhiyuan Li, Hailong Li, Adebayo Braimah, Jonathan R. Dillman, Nehal A. Parikh, Lili He

NeuroImage, 2022

Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology.

Julia E. Kline, Jonathan Dudley, Venkata Sita Priyanka Illapani, Hailong Li, Beth Kline-Fath, Jean A. Tkach, Lili He, Weihong Yuan, Nehal A. Parikh

NeuroImage, 2022

2021

Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants.

Julia E. Kline, Weihong Yuan, Karen Harpster, Mekibib Altaye, Nehal A. Parikh

NeuroImage, 2021

2013

Automated detection of white matter signal abnormality using T2 relaxometry: Application to brain segmentation on term MRI in very preterm infants.

Lili He, Nehal A. Parikh

NeuroImage, 2013