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Enhao Gong

Palo Alto University · US
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Area of research
Radiology, Nuclear Medicine and Imaging · Endocrinology, Diabetes and Metabolism
Research interest
Research interests include Medicine, Magnetic resonance imaging, Computer science, Perfusion, Nuclear medicine, and Artificial intelligence.
h-index
citations
279
works
10
NIH funding
primary concept
email

Recent publications

Abstract 8: Hypoperfusion Lesion And Target Mismatch Prediction In Acute Ischemic Stroke From Baseline Mr Diffusion Imaging Using A 3d Convolutional Neural Network
Stroke 2022cited by 1position: middledoi
Low-count whole-body PET with deep learning in a multicenter and externally validated study
npj Digital Medicine 2021cited by 70position: middledoi
Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis
Frontiers in Neurology 2021cited by 28position: middledoi
Author Correction: Low-count whole-body PET with deep learning in a multicenter and externally validated study
npj Digital Medicine 2021cited by 2position: middledoi
Abstract P319: Can Deep Learning Find the Ischemic Core on CT? Transfer Learning From Pre-Trained MRI-Based Networks
Stroke 2021cited by 0position: middledoi
Abstract P325: Validation of Deep Learning Based Critical Hypoperfusion and Ischemic Core Prediction in a Multicenter External Randomized Controlled Trial
Stroke 2021cited by 0position: middledoi
Joint multi‐contrast variational network reconstruction (jVN) with application to rapid 2D and 3D imaging
Magnetic Resonance in Medicine 2020cited by 10position: middledoi
Abstract WP79: The Value of Pre-Training for Deep Learning Acute Stroke Triaging Models
Stroke 2020cited by 0position: middledoi
Abstract WMP19: Prediction of Subacute Infarction in Acute Ischemic Stroke Using Baseline Multi-modal MRI and Deep Learning
Stroke 2019cited by 0position: middledoi
ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI
Frontiers in Neurology 2018cited by 168position: middledoi

Grants

No grants ingested yet.

Frequent collaborators

Greg Zaharchuk · Stanford University7 papers (2019–2022)Yannan Yu · The University of Sydney5 papers (2019–2022)Maarten G. Lansberg · Stanford University4 papers (2020–2022)Yuan Xie · Tongji University4 papers (2019–2021)Gregory W. Albers · Stanford University4 papers (2020–2022)Sören Christensen · Duke University3 papers (2020–2022)Thoralf Thamm · Stanford University2 papers (2019–2020)Hossein Jadvar · University of Southern California2 papers (2021–2021)Akshay Chaudhari · Stanford University2 papers (2021–2021) · 2 papers (2021–2021)Jiahong Ouyang · Palo Alto University2 papers (2020–2022) · 2 papers (2021–2021)Shyam Srinivas · UCLA Health2 papers (2021–2021)Erik Mittra · Oregon Health & Science University2 papers (2021–2021)Praveen Gulaka · Southwestern Medical Center2 papers (2021–2021)Guido Davidzon · Palo Alto University2 papers (2021–2021)Tao Zhang · Chongqing University2 papers (2021–2021)Cigdem Isitan · Boston Medical Center1 papers (2021–2021)Shruthi Venkatesh · Northeastern University1 papers (2021–2021)Ashika Mani · University of Pittsburgh Medical Center1 papers (2021–2021)
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