CNL Publication Index: BibTeX
This database contains all the publications of Terrence J. Sejnowski starting in 1969.
Most of these publications can be downloaded in PDF format. They are made available for individual use only; contact the publisher and the author to receive permission for reproduction in any form.
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Found 10
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21 Total.
- Goldbaum, M. Sample, P. A. Zhang, Z. Chan, K. Hao, J, Lee T.-W. Boden, C. Bourne, R. Zangwill, L. A. Sejnowski, T. J. Spinak, D. Weinreb, R. N. Using unsupervised learning with independent component analysis to identify patterns of glaucomatous visual field defects, Investigative Ophthalmology and Visual Science, 46(10):3676-83, 2005 PMCID:PMC1866286 (PDF)
- Bowd, C. Zangwill, L. M. Medeiros, F. A. Hao, J. Chan, K. Lee, T.W. Sejnowski, T. J. Goldbaum, M. H. Sample, P. A. Crowston, J. G. Weinberg, R. J. Confocal Scanning Laser Ophthalmoscopy Classifiers and Stereophotograph Evaluation for Prediction of Visual Field Abnormalities in Glaucoma-Suspect Eyes, Investigative Ophthalmology & Visual Science, 45(7) 2255-2262, 2004 (PDF)
- Zangwill, L. M. Chan, K. Bowd, C. Hao, J. Lee, T.-W. Weinberg, R. J. Sejnowski, T. J. Goldbaum, M. H. Heidelberg Retina Tomograph Measurements of the Optic Disc and Parapapillary Retina for Detecting Glaucoma Analyzed by Machine Learning Classifiers, Investigative Ophthalmology & Visual Science, 45(9) 3144-3151, 2004 (PDF)
- Sample, P. A. Chan, K. Boden, C. Lee, T.-W. Blumenthal, E. Z. Weinberg, R. J. Bernd, A. Pascual, J. Hao, J. Sejnowski, T. J. Goldbaum, M. H. Using Unsupervised Learning with Variational Bayesian Mixture of Factor Analysis to Identify Patterns of Glaucomatous Visual Field Defects, Investigative Ophthalmology & Visual Science, 45(8) 2596-2605, 2004 (PDF)
- Chan, K. Lee, T.-W. Sejnowski, T. J. Variational Bayesian Learning of ICA with Missing Data, Neural Computation, 15, 1991–2011, 2003 (PDF)
- Sample, P. A. Goldbaum, M. H. Chan, K. Boden, C. Lee, T.-W. Vasile, C. Boehm, A. G. Sejnowski, T. J. Johnson, C. A. Weinberg, R. J. Using Machine Learning Classifiers to Identify Glaucomatous Change Earlier in Standard Visual Fields, Investigative Ophthalmology & Visual Science, 43(8) 2660-2665, 2002 (PDF)
- Goldbaum, M. H. Sample, P. A. Chan, K. Williams, J. Lee, T.-W. Blumenthal, E. Z. Girkin, C. A. Zangwill, L. M. Bowd, C. Sejnowski, T. J. Weinberg, R. J. Comparing Machine Learning Classifiers for Diagnosing Glaucoma from Standard Automated Perimetry, Investigative Ophthalmology & Visual Science, Vol. 43, No. 1, 2002 (PDF)
- Bowd, C. Chan, K. Zangwill, L. M. Goldbaum, M. H. Lee, T. W. Sejnowski, T. J. Weinberg, R. J. Comparing Neural Networks and Linear Discriminant Functions for Glaucoma Detection Using Confocal Scanning Laser Ophthalmoscopy of the Optic Disc, Investigative Ophthalmology & Visual Science, Vol. 43, No. 11, 2002 (PDF)
- Chan, K. Lee, T.W. Sample, P. A. Goldbaum, M. H. Weinberg, R. J. Sejnowski, T. J. Comparison of Machine Learning and Traditional Classifiers in Glaucoma Diagnosis - Biomedical Engineering, IEEE Transactions on Biomedical Engineering, 49(9) 963-974, 2002 (PDF)
- Chan, K. Lee, T.-W. Sejnowski, T. J. Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components, Journal of Machine Learning Research, 3, 99-114, 2002 (PDF)
- Bowd, C. Medeiros, F. A. Zangwill, L. M. Zhang, Z. Hao, J. Chan, K. Lee, T.–W. Goldbaum, M. H. Sejnowski, T. J. Weinreb, R. N. Support Vector Machine Analysis of VCC Scanning Laser Polarimetry RNFL Thickness Measurements, Invest. Ophthalmol. Vis. Sci., 45: 3405, 2004 (PDF)
- Sample, P. A. Zhang, Z. Pascual, J. Chan, K. Boden, C. Hao, J. Lee, T.–W. Weinreb, R. N. Sejnowski, T. J. Goldbaum, M Unsupervised Machine Learning with Independent Component Analysis Identifies Areas of Progression in Glaucomatous Visual Fields, Investigative Ophthalmology and Visual Science, 45: 3471, 2004 (PDF)
- Boden, C. Chan, K. Goldbaum, M. Lee, T. Sejnowski, T. J. Hao, J. Vasile, C. Medeiros, F. A. Weinreb, R. N. Sample, P. A. Assessing Validity of Visual Field Clustering Schemes for Standard Perimetry Using Machine Learning Classifiers, Invest. Ophthalmol. Vis. Sci., 44: 60, 2003 (PDF)
- Zangwill, L. M. Chan, K. Bowd, C. Medeiros, F. Goldbaum, M. H. Lee, T. Sejnowski, T. J. Weinreb, R. N. Comparing Confocal Scanning Laser Ophthalmoscopy Measurements of the Optic Nerve Head and Peripapillary Retina for Detecting Glaucoma using Machine Learning Classifiers, Invest. Ophthalmol. Vis. Sci., 44: 981, 2003 (PDF)
- Goldbaum, M. H. Sample, P.A. Chan, K. Lee, T. McGuire, D. Sejnowski, T. J. Weinreb, R. N. Shortened Perimetry for Glaucoma With Top 10 Locations Derived by Feature Selection With Machine Learning Classifiers, Invest. Ophthalmol. Vis. Sci., 44: 1041, 2003 (PDF)
- Goldbaum, M. H. Sample, P. A. Chan, K. Lee, T.-W. McGuire, D. Sejnowski, T. J. Weinreb, R. N. Analysis of Glaucomatous Visual Field Patterns Found with Unsupervised Learning Using Independent Component Analysis and Principal Component Analysis, The Association for Research in Vision and Ophthalmology Abstracts, 43:S2178, 2002 (PDF)
- Boden, C. Chan, K. Goldbaum, M. Lee, T.-W. Sejnowski, T. J. Boehm, A. G. Aihara, M. Weinreb, R. N. Sample, P. A. Machine Learning Classifiers in the Diagnosis and Follow-Up of Glaucoma Using Short-Wavelength Automated Perimetry (SWAP), The Association for Research in Vision and Ophthalmology Abstracts, 43:S2127, 2002 (PDF)
- Sample, P. A. Goldbaum, M. H. Chan, K. Boden, C. Lee, T.-W. Boehm, A. Vasile, C. Sejnowski, T. J. Johnson, C. A. Weinreb,R. N Predicting Development of Abnormal Standard Visual Fields in Ocular Hypertensive Eyes: Machine Learning Classifiers and Statpac-Like Analysis, The Association for Research in Vision and Ophthalmology Abstracts, 43:S1939, 2002 (PDF)
- Sample, P. A. Goldbaum, M. H. Chan, K.-L. Boden, C. Lee, T.-W. Sejnowski, T. J. Johnson, C. A. Weinreb, R. N. Machine Classifiers Predict Development of Abnormal Standard Visual Fields in Ocular Hypertensive Eyes, North American Permetric Society Meeting, Skaneateles, New York, 2001 (PDF)
- Chan, K. Zhang, K. Knierim, J. J. McNaughton, B. L. Sejnowski, T. J. Comparison of Different Methods for Position Reconstruction from Hippocampal Place Cell Recordings, Society for Neuroscience Abstracts, 25, 2166, 1999 (PDF)