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Michael H Goldbaum

Showing results (11-20 of 65) with videos related to

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Proceedings of Spie--The International Society for Optical Engineering|January 17, 2015
Recognizing patterns of visual field loss using unsupervised machine learningSiamak Yousefi, Michael H Goldbaum, Linda M Zangwill, et al.
Survey of Ophthalmology|October 13, 2017
Optic nerve head problemRohan Verma, Kevin C Chen, Hema L Ramkumar, et al.
Ocular Oncology and Pathology|August 2, 2019
GNAQ and PMS1 Mutations Associated with Uveal Melanoma, Ocular Surface Melanosis, and Nevus of OtaChristopher B Toomey, Kyle Fraser, John A Thorson, et al.
Journal of Refractive Surgery (Thorofare, N.J. : 1995)|May 10, 2023
Refractive Changes After Implantation of Reversed Intraocular Lens in Cataract Surgery: A Mathematical ModelHongseok Yang, Hedieh Matinrad, Michael H Goldbaum, et al.
Journal of the American College of Cardiology|October 17, 2025
The Retinal Fundus Verdict on Intensive Blood-Pressure Therapy: Lower Is BetterMathieu F Bakhoum, Michael K Wong, Christina J Jayaraj, et al.
Journal of Ophthalmology|October 21, 2022
Clinical Outcomes Comparison of Combined Small Incision Lenticule Extraction with Collagen Cross-Linking Versus Small Incision Lenticule Extraction OnlyAyoub Chabib, Massimo Mammone, Chiara Fantozzi, et al.
Graefe'S Archive for Clinical and Experimental Ophthalmology = Albrecht Von Graefes Archiv Fur Klinische Und Experimentelle Ophthalmologie|September 25, 2010
Pattern recognition can detect subtle field defects in eyes of HIV individuals without retinitis under HAARTMichael H Goldbaum, Igor Kozak, Jiucang Hao, et al.
Transactions of the American Ophthalmological Society|March 12, 2009
Analysis with support vector machine shows HIV-positive subjects without infectious retinitis have mfERG deficiencies compared to normal eyesMichael H Goldbaum, Irina Falkenstein, Igor Kozak, et al.
IEEE Transactions on Bio-Medical Engineering|September 7, 2002
Comparison of machine learning and traditional classifiers in glaucoma diagnosisKwokleung Chan, Te-Won Lee, Pamela A Sample, et al.
Transactions of the American Ophthalmological Society|April 23, 2008
Machine learning classifiers detect subtle field defects in eyes of HIV individualsIgor Kozak, Pamela A Sample, Jiucang Hao, et al.
Pageof 7

Showing results (11-20 of 65) with videos related to

Sort By:
Pageof 7
Proceedings of Spie--The International Society for Optical Engineering|January 17, 2015
Recognizing patterns of visual field loss using unsupervised machine learningSiamak Yousefi, Michael H Goldbaum, Linda M Zangwill, et al.
Survey of Ophthalmology|October 13, 2017
Optic nerve head problemRohan Verma, Kevin C Chen, Hema L Ramkumar, et al.
Ocular Oncology and Pathology|August 2, 2019
GNAQ and PMS1 Mutations Associated with Uveal Melanoma, Ocular Surface Melanosis, and Nevus of OtaChristopher B Toomey, Kyle Fraser, John A Thorson, et al.
Journal of Refractive Surgery (Thorofare, N.J. : 1995)|May 10, 2023
Refractive Changes After Implantation of Reversed Intraocular Lens in Cataract Surgery: A Mathematical ModelHongseok Yang, Hedieh Matinrad, Michael H Goldbaum, et al.
Journal of the American College of Cardiology|October 17, 2025
The Retinal Fundus Verdict on Intensive Blood-Pressure Therapy: Lower Is BetterMathieu F Bakhoum, Michael K Wong, Christina J Jayaraj, et al.
Journal of Ophthalmology|October 21, 2022
Clinical Outcomes Comparison of Combined Small Incision Lenticule Extraction with Collagen Cross-Linking Versus Small Incision Lenticule Extraction OnlyAyoub Chabib, Massimo Mammone, Chiara Fantozzi, et al.
Graefe'S Archive for Clinical and Experimental Ophthalmology = Albrecht Von Graefes Archiv Fur Klinische Und Experimentelle Ophthalmologie|September 25, 2010
Pattern recognition can detect subtle field defects in eyes of HIV individuals without retinitis under HAARTMichael H Goldbaum, Igor Kozak, Jiucang Hao, et al.
Transactions of the American Ophthalmological Society|March 12, 2009
Analysis with support vector machine shows HIV-positive subjects without infectious retinitis have mfERG deficiencies compared to normal eyesMichael H Goldbaum, Irina Falkenstein, Igor Kozak, et al.
IEEE Transactions on Bio-Medical Engineering|September 7, 2002
Comparison of machine learning and traditional classifiers in glaucoma diagnosisKwokleung Chan, Te-Won Lee, Pamela A Sample, et al.
Transactions of the American Ophthalmological Society|April 23, 2008
Machine learning classifiers detect subtle field defects in eyes of HIV individualsIgor Kozak, Pamela A Sample, Jiucang Hao, et al.
Pageof 7