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Jordan J Bannister

Showing results (1-10 of 12) with videos related to

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Frontiers in Aging Neuroscience|September 8, 2022
An exploratory causal analysis of the relationships between the brain age gap and cardiovascular risk factorsPauline Mouches, Matthias Wilms, Jordan J Bannister, et al.
Facial Plastic Surgery & Aesthetic Medicine|August 31, 2023
Response to Jacobs and Flaherty re: "Sex Differences in Adult Facial Three-Dimensional Morphology: Application to Gender-Affirming Facial Surgery"Rahul Seth, Jordan J Bannister, David C Katz, et al.
IEEE Transactions on Medical Imaging|March 24, 2022
Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain AgingMatthias Wilms, Jordan J Bannister, Pauline Mouches, et al.
Facial Plastic Surgery & Aesthetic Medicine|March 31, 2022
Sex Differences in Adult Facial Three-Dimensional Morphology: Application to Gender-Affirming Facial SurgeryJordan J Bannister, Hailey Juszczak, Jose David Aponte, et al.
European Journal of Human Genetics : EJHG|February 7, 2023
Comparing 2D and 3D representations for face-based genetic syndrome diagnosisJordan J Bannister, Matthias Wilms, J David Aponte, et al.
Artificial Intelligence in Medicine|December 3, 2022
Detecting 3D syndromic faces as outliers using unsupervised normalizing flow modelsJordan J Bannister, Matthias Wilms, J David Aponte, et al.
IEEE Journal of Biomedical and Health Informatics|April 5, 2022
A Deep Invertible 3-D Facial Shape Model for Interpretable Genetic Syndrome DiagnosisJordan J Bannister, Matthias Wilms, J David Aponte, et al.
Sensors (Basel, Switzerland)|June 7, 2020
Fully Automatic Landmarking of Syndromic 3D Facial Surface Scans Using 2D ImagesJordan J Bannister, Sebastian R Crites, J David Aponte, et al.
Journal of Anatomy|January 13, 2017
Rapid automated landmarking for morphometric analysis of three-dimensional facial scansMao Li, Joanne B Cole, Mange Manyama, et al.
Journal of Neural Engineering|October 9, 2020
Supervised machine learning tools: a tutorial for cliniciansLucas Lo Vercio, Kimberly Amador, Jordan J Bannister, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Frontiers in Aging Neuroscience|September 8, 2022
An exploratory causal analysis of the relationships between the brain age gap and cardiovascular risk factorsPauline Mouches, Matthias Wilms, Jordan J Bannister, et al.
Facial Plastic Surgery & Aesthetic Medicine|August 31, 2023
Response to Jacobs and Flaherty re: "Sex Differences in Adult Facial Three-Dimensional Morphology: Application to Gender-Affirming Facial Surgery"Rahul Seth, Jordan J Bannister, David C Katz, et al.
IEEE Transactions on Medical Imaging|March 24, 2022
Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain AgingMatthias Wilms, Jordan J Bannister, Pauline Mouches, et al.
Facial Plastic Surgery & Aesthetic Medicine|March 31, 2022
Sex Differences in Adult Facial Three-Dimensional Morphology: Application to Gender-Affirming Facial SurgeryJordan J Bannister, Hailey Juszczak, Jose David Aponte, et al.
European Journal of Human Genetics : EJHG|February 7, 2023
Comparing 2D and 3D representations for face-based genetic syndrome diagnosisJordan J Bannister, Matthias Wilms, J David Aponte, et al.
Artificial Intelligence in Medicine|December 3, 2022
Detecting 3D syndromic faces as outliers using unsupervised normalizing flow modelsJordan J Bannister, Matthias Wilms, J David Aponte, et al.
IEEE Journal of Biomedical and Health Informatics|April 5, 2022
A Deep Invertible 3-D Facial Shape Model for Interpretable Genetic Syndrome DiagnosisJordan J Bannister, Matthias Wilms, J David Aponte, et al.
Sensors (Basel, Switzerland)|June 7, 2020
Fully Automatic Landmarking of Syndromic 3D Facial Surface Scans Using 2D ImagesJordan J Bannister, Sebastian R Crites, J David Aponte, et al.
Journal of Anatomy|January 13, 2017
Rapid automated landmarking for morphometric analysis of three-dimensional facial scansMao Li, Joanne B Cole, Mange Manyama, et al.
Journal of Neural Engineering|October 9, 2020
Supervised machine learning tools: a tutorial for cliniciansLucas Lo Vercio, Kimberly Amador, Jordan J Bannister, et al.
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