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Author Details

Diane Villaroman
University of California los angeles
2017
8
7
PMIDPaper TitleJournal TitlePublished Year
37225710A pilot study of closed-loop neuromodulation for treatment-resistant post-traumatic stress disorder.Nat Commun2023
37225710A pilot study of closed-loop neuromodulation for treatment-resistant post-traumatic stress disorder.Nat Commun2023
33361808Boundary-anchored neural mechanisms of location-encoding for self and others.Nature2021
33826737Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.Neurosurgery2021
33361808Boundary-anchored neural mechanisms of location-encoding for self and others.Nature2021
33826737Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.Neurosurgery2021
31467240Quantitative Analysis of Spinal Canal Areas in the Lumbar Spine: An Imaging Informatics and Machine Learning Study.AJNR Am J Neuroradiol2019
31561232Natural history of the aging spine: a cross-sectional analysis of spinopelvic parameters in the asymptomatic population.J Neurosurg Spine2019
33937788Quantitative Analysis of Neural Foramina in the Lumbar Spine: An Imaging Informatics and Machine Learning Study.Radiol Artif Intell2019
31469647A Novel Mobile Tool (Somatomap) to Assess Body Image Perception Pilot Tested With Fashion Models and Nonmodels: Cross-Sectional Study.JMIR Ment Health2019
31467240Quantitative Analysis of Spinal Canal Areas in the Lumbar Spine: An Imaging Informatics and Machine Learning Study.AJNR Am J Neuroradiol2019
33937788Quantitative Analysis of Neural Foramina in the Lumbar Spine: An Imaging Informatics and Machine Learning Study.Radiol Artif Intell2019
31561232Natural history of the aging spine: a cross-sectional analysis of spinopelvic parameters in the asymptomatic population.J Neurosurg Spine2019
31469647A Novel Mobile Tool (Somatomap) to Assess Body Image Perception Pilot Tested With Fashion Models and Nonmodels: Cross-Sectional Study.JMIR Ment Health2019
29018631Multi-Parameter Ensemble Learning for Automated Vertebral Body Segmentation in Heterogeneously Acquired Clinical MR Images.IEEE J Transl Eng Health Med2017
29018631Multi-Parameter Ensemble Learning for Automated Vertebral Body Segmentation in Heterogeneously Acquired Clinical MR Images.IEEE J Transl Eng Health Med2017
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Collaborators

Mark A Attiah
Kaiser Permanente Los Angeles Medical Center
Co-authored papers 5
Luke Macyszyn
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 5
Joel S Beckett
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 5
Bilwaj Gaonkar
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 5
Juan Pablo Villablanca
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 2
Noriko Salamon
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 2
Christopher P Ames
Co-authored papers 2
Alex A T Bui
University of California Los Angeles
Co-authored papers 2
Diana Babayan
University of California Los Angeles
Co-authored papers 2
Alex A T Bui
Co-authored papers 2
Steven Moran
Co-authored papers 1
Azim Laiwalla
University of California Los Angeles
Co-authored papers 1
Bryan Yoo
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 1
Armen C Arevian
university of california los angeles Semel Institute
Co-authored papers 1
Matthew Edwards
Co-authored papers 1
Banafsheh Salehi
David Geffen School of Medicine at University of California Los Angeles
Co-authored papers 1
Bayard Wilson
David Geffen School of Medicine, University of California Los Angeles
Co-authored papers 1
Release 1.2