Michael Goldbaum
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Identifying medical diagnoses and treatable diseases by image-based deep learning
DS Kermany, M Goldbaum, W Cai, CCS Valentim, H Liang, SL Baxter, ...
cell 172 (5), 1122-1131. e9, 2018
Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response
AD Hoover, V Kouznetsova, M Goldbaum
IEEE Transactions on Medical imaging 19 (3), 203-210, 2000
Detection of blood vessels in retinal images using two-dimensional matched filters
S Chaudhuri, S Chatterjee, N Katz, M Nelson, M Goldbaum
IEEE Transactions on medical imaging 8 (3), 263-269, 1989
Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels
A Hoover, M Goldbaum
IEEE transactions on medical imaging 22 (8), 951-958, 2003
Labeled optical coherence tomography (oct) and chest x-ray images for classification
D Kermany, K Zhang, M Goldbaum
Mendeley data 2 (2), 651, 2018
Beneficial effects of intensive therapy of diabetes during adolescence: outcomes after the conclusion of the Diabetes Control and Complications Trial (DCCT)
PA Cleary, W Dahms, D Goldstein, J Malone, WV Tamborlane
J Pediatr 139 (1), 804-12, 2001
Sustained effect of intensive treatment of type 1 diabetes mellitus on development and progression of diabetic nephropathy: the Epidemiology of Diabetes Interventions and …
TWT for the Diabetes, ...
JAMA: the journal of the American Medical Association 290 (16), 2159, 2003
Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence
H Liang, BY Tsui, H Ni, CCS Valentim, SL Baxter, G Liu, W Cai, ...
Nature medicine 25 (3), 433-438, 2019
Measurement and classification of retinal vascular tortuosity
WE Hart, M Goldbaum, B Côté, P Kube, MR Nelson
International journal of medical informatics 53 (2-3), 239-252, 1999
Performance of deep learning architectures and transfer learning for detecting glaucomatous optic neuropathy in fundus photographs
M Christopher, A Belghith, C Bowd, JA Proudfoot, MH Goldbaum, ...
Scientific reports 8 (1), 16685, 2018
Comparison of machine learning and traditional classifiers in glaucoma diagnosis
K Chan, TW Lee, PA Sample, MH Goldbaum, RN Weinreb, TJ Sejnowski
IEEE Transactions on Biomedical Engineering 49 (9), 963-974, 2002
Automated diagnosis and image understanding with object extraction, object classification, and inferencing in retinal images
M Goldbaum, S Moezzi, A Taylor, S Chatterjee, J Boyd, E Hunter, R Jain
Proceedings of 3rd IEEE international conference on image processing 3, 695-698, 1996
Large dataset of labeled optical coherence tomography (oct) and chest x-ray images
D Kermany, K Zhang, M Goldbaum
Mendeley Data 3 (10.17632), 2018
Silicone oil tamponade to seal macular holes without position restrictions
MH Goldbaum, BW McCuen 2nd, AM Hanneken, SK Burgess, HH Chen
Ophthalmology 105 (11), 2140-2148, 1998
Comparing machine learning classifiers for diagnosing glaucoma from standard automated perimetry
MH Goldbaum, PA Sample, K Chan, J Williams, TW Lee, E Blumenthal, ...
Investigative ophthalmology & visual science 43 (1), 162-169, 2002
Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic disc
C Bowd, K Chan, LM Zangwill, MH Goldbaum, TW Lee, TJ Sejnowski, ...
Investigative ophthalmology & visual science 43 (11), 3444-3454, 2002
Interpretation of automated perimetry for glaucoma by neural network.
MH Goldbaum, PA Sample, H White, B Colt, P Raphaelian, RD Fechtner, ...
Investigative ophthalmology & visual science 35 (9), 3362-3373, 1994
Deep learning approaches predict glaucomatous visual field damage from OCT optic nerve head en face images and retinal nerve fiber layer thickness maps
M Christopher, C Bowd, A Belghith, MH Goldbaum, RN Weinreb, ...
Ophthalmology 127 (3), 346-356, 2020
Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiers
LM Zangwill, K Chan, C Bowd, J Hao, TW Lee, RN Weinreb, TJ Sejnowski, ...
Investigative ophthalmology & visual science 45 (9), 3144-3151, 2004
Retinal nerve fiber layer features identified by unsupervised machine learning on optical coherence tomography scans predict glaucoma progression
M Christopher, A Belghith, RN Weinreb, C Bowd, MH Goldbaum, ...
Investigative ophthalmology & visual science 59 (7), 2748-2756, 2018
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