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A deep transfer learning model for early prediction of cognitive deficits using brain structural connectome data in very preterm infants

Author:Ming Chen Hailong Li Jinghua Wang Weihong Yuan Adebayo Brainmah Mekibib Altaye Nehal Parikh Lili He

Institution:Cincinnati Children's Hospital Medical Center University of Cincinnati College of Medicine University of Cincinnati

Session Type:Digital Poster

Session Live Q&A Date:Digital Poster (All Week)

Topic:Pediatric: Brain Structure & Function

Session Name:Pediatric Technical Advances

Program Number:4628

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A Deep Transfer Learning Model to Predict Patient Outcome in ICH using the Fusion of Clinical and Fluid-Attenuated Inversion Recovery Imaging Data

Author:Jinghua Wang Ming Chen Lili He Hailong Li Vivek Khandwala David Wang Brady Williamson Daniel Woo Achala Vagal

Institution:Cincinnati Children’s Hospital Medical Center University of Cincinnati

Session Type:Digital Poster

Session Live Q&A Date:Digital Poster (All Week)

Topic:Neuroimaging and AI

Session Name:Neuroimaging & AI: Tumour & Hemorrhage

Program Number:1909

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Early prediction of neurodevelopmental deficits in very preterm infants using a multi-task deep transfer learning model

Author:Lili He Hailong Li Jinghua Wang Ming Chen Jonathan Dillman Nehal Parikh

Institution:Cincinnati Children's Hospital Medical Center University of Cincinnati University of Cincinnati College of Medicine

Session Type:Digital Poster

Session Live Q&A Date:Digital Poster (All Week)

Topic:Pediatric: Brain Structure & Function

Session Name:Pediatric Technical Advances

Program Number:4629

Room Live Q&A Session:

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A machine learning model using T2-weighted FLAIR radiomics features to predict patient outcome in ICH

Author:Jinghua Wang Ming Chen Lili He Hailong Li Vivek Khandwala David Wang Brady Williamson Daniel Woo Achala Vagal

Institution:Cincinnati Children’s Hospital Medical Center University of Cincinnati

Session Type:Digital Poster

Session Live Q&A Date:Digital Poster (All Week)

Topic:Neuroimaging and AI

Session Name:Neuroimaging & AI: Tumour & Hemorrhage

Program Number:1910

Room Live Q&A Session:

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A deep transfer learning model for early prediction of cognitive deficits using brain structural connectome data in very preterm infants

A Deep Transfer Learning Model to Predict Patient Outcome in ICH using the Fusion of Clinical and Fluid-Attenuated Inversion Recovery Imaging Data

Early prediction of neurodevelopmental deficits in very preterm infants using a multi-task deep transfer learning model

A machine learning model using T2-weighted FLAIR radiomics features to predict patient outcome in ICH