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Keshi He

Showing results (1-10 of 8) with videos related to

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IEEE Journal of Biomedical and Health Informatics|November 26, 2025
Deep Learning for Clinical Ultrasound Imaging: From Supervised Approaches to Foundation ModelsKeshi He, Donglai Wei, Bryan Ranger
IEEE Journal of Biomedical and Health Informatics|July 11, 2018
Ultrasound-Based Sensing Models for Finger Motion ClassificationYoujia Huang, Xingchen Yang, Yuefeng Li, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 3, 2025
Improving Ultrasound Image Segmentation in Data-Scarce Scenarios Using Self-Supervised Learning With Phantom Data Pre-TrainingBo Jiang, Keshi He, Hayoung Cho, et al.
Acta Paediatrica (Oslo, Norway : 1992)|September 19, 2024
Ultrasound for assessing paediatric body composition and nutritional status: Scoping review and future directionsBryan J Ranger, Allison Lombardi, Susie Kwon, et al.
ACS Omega|September 8, 2025
Ultrasound Imaging and Machine Learning for Nondestructive Sensing in BioreactorsMary Serpe, Caleb Lee, Reid Povinelli, et al.
IEEE Access : Practical Innovations, Open Solutions|January 26, 2026
Developing a Deep Learning Approach for Automated Body Composition Prediction in Newborns Using Ultrasound ImagesKeshi He, Y I Li, Hayoung Cho, et al.
Ultrasound in Medicine & Biology|October 16, 2025
Enhancing Newborn Health Assessment: Ultrasound-based Body Composition Prediction Using Deep Learning TechniquesKeshi He, Julia Hohenberg, Yi Li, et al.
Pilot and Feasibility Studies|April 5, 2026
A machine learning approach to using ultrasound for body composition and nutritional status assessment in newborns: a pilot study protocolBryan J Ranger, Marisa Albert, Ji In Kim, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
IEEE Journal of Biomedical and Health Informatics|November 26, 2025
Deep Learning for Clinical Ultrasound Imaging: From Supervised Approaches to Foundation ModelsKeshi He, Donglai Wei, Bryan Ranger
IEEE Journal of Biomedical and Health Informatics|July 11, 2018
Ultrasound-Based Sensing Models for Finger Motion ClassificationYoujia Huang, Xingchen Yang, Yuefeng Li, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 3, 2025
Improving Ultrasound Image Segmentation in Data-Scarce Scenarios Using Self-Supervised Learning With Phantom Data Pre-TrainingBo Jiang, Keshi He, Hayoung Cho, et al.
Acta Paediatrica (Oslo, Norway : 1992)|September 19, 2024
Ultrasound for assessing paediatric body composition and nutritional status: Scoping review and future directionsBryan J Ranger, Allison Lombardi, Susie Kwon, et al.
ACS Omega|September 8, 2025
Ultrasound Imaging and Machine Learning for Nondestructive Sensing in BioreactorsMary Serpe, Caleb Lee, Reid Povinelli, et al.
IEEE Access : Practical Innovations, Open Solutions|January 26, 2026
Developing a Deep Learning Approach for Automated Body Composition Prediction in Newborns Using Ultrasound ImagesKeshi He, Y I Li, Hayoung Cho, et al.
Ultrasound in Medicine & Biology|October 16, 2025
Enhancing Newborn Health Assessment: Ultrasound-based Body Composition Prediction Using Deep Learning TechniquesKeshi He, Julia Hohenberg, Yi Li, et al.
Pilot and Feasibility Studies|April 5, 2026
A machine learning approach to using ultrasound for body composition and nutritional status assessment in newborns: a pilot study protocolBryan J Ranger, Marisa Albert, Ji In Kim, et al.
Pageof 1