Cikkek nyilvánosan hozzáférhető megbízással - Dmitry GoldgofTovábbi információ
Sehol sem hozzáférhető: 18
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
R Paul, SH Hawkins, LO Hall, DB Goldgof, RJ Gillies
2016 IEEE international conference on systems, man, and cybernetics (SMC …, 2016
Megbízások: US National Science Foundation, US National Institutes of Health
Convergence of the single-pass and online fuzzy c-means algorithms
LO Hall, DB Goldgof
IEEE Transactions on Fuzzy Systems 19 (4), 792-794, 2011
Megbízások: US National Institutes of Health
Effect of texture features in computer aided diagnosis of pulmonary nodules in low-dose computed tomography
H Krewer, B Geiger, LO Hall, DB Goldgof, Y Gu, M Tockman, RJ Gillies
2013 IEEE International Conference on Systems, Man, and Cybernetics, 3887-3891, 2013
Megbízások: US National Institutes of Health
Evaluation and optimization of remote sensing techniques for detection of Karenia brevis blooms on the West Florida Shelf
IM Soto, J Cannizzaro, FE Muller-Karger, C Hu, J Wolny, D Goldgof
Remote Sensing of Environment 170, 239-254, 2015
Megbízások: US National Aeronautics and Space Administration
Iterative feature perturbation as a gene selector for microarray data
J Canul-Reich, LO Hall, DB Goldgof, JN Korecki, S Eschrich
International Journal of Pattern Recognition and Artificial Intelligence 26 …, 2012
Megbízások: US National Institutes of Health
A texture feature ranking model for predicting survival time of brain tumor patients
M Zhou, LO Hall, DB Goldgof, RA Gatenby, RJ Gillies
2013 IEEE International Conference on Systems, Man, and Cybernetics, 4533-4538, 2013
Megbízások: US National Institutes of Health
Deep radiomics: deep learning on radiomics texture images
R Paul, S Kariev, D Cherezov, MB Schabath, RJ Gillies, LO Hall, ...
Medical Imaging 2021: Computer-Aided Diagnosis 11597, 8-17, 2021
Megbízások: US National Science Foundation, US Department of Defense, US National …
Evaluating scalable fuzzy clustering
Y Gu, LO Hall, DB Goldgof
2010 IEEE International Conference on Systems, Man and Cybernetics, 873-880, 2010
Megbízások: US National Institutes of Health
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images
R Paul, D Cherezov, MB Schabath, RJ Gillies, LO Hall, DB Goldgof
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 997-1003, 2019
Megbízások: US National Science Foundation, US National Institutes of Health
A novel deep learning-based method for automatic stereology of microglia cells from low magnification images
H Morera, P Dave, Y Kolinko, S Alahmari, A Anderson, G Denham, ...
Neurotoxicology and Teratology 102, 107336, 2024
Megbízások: US National Science Foundation, US National Institutes of Health
Enhancing neonatal pain assessment transparency via explanatory training examples identification
MI Hossain, G Zamzmi, P Mouton, Y Sun, D Goldgof
2023 IEEE 36th International Symposium on Computer-Based Medical Systems …, 2023
Megbízások: US National Institutes of Health
Automatic location of microscopic focal planes for computerized stereology
DT Elozory, OP Bonam, K Kramer, DB Goldgof, LO Hall, O Mangual, ...
Medical Imaging 2011: Computer-Aided Diagnosis 7963, 956-962, 2011
Megbízások: US National Institutes of Health
Automatic pressure ulcer measurement using RGB-D data
CY Pai, H Morera, S Sarkar, K Hall, L Cowan, PA Toyinbo, MJ Peterson, ...
Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and …, 2019
Megbízások: US Department of Defense
Survival time prediction from unannotated lung cancer histopathology images
N Fetisov, LO Hall, DB Goldgof, MB Schabath
Medical Imaging 2022: Digital and Computational Pathology 12039, 291-298, 2022
Megbízások: US National Institutes of Health
Change descriptors for determining nodule malignancy in National Lung Screening Trial CT screening images
B Geiger, S Hawkins, LO Hall, DB Goldgof, Y Balagurunathan, ...
Medical Imaging 2016: Computer-Aided Diagnosis 9785, 805-811, 2016
Megbízások: US National Institutes of Health
A novel algorithm for automated counting of stained cells on thick tissue sections
B Chaudhury, K Kramer, D Elozory, G Hernandez, D Goldgof, LO Hall, ...
2012 25th IEEE International Symposium on Computer-Based Medical Systems …, 2012
Megbízások: US National Institutes of Health
Ant clustering using ensembles of partitions
Y Gu, LO Hall, DB Goldgof
Multiple Classifier Systems: 8th International Workshop, MCS 2009, Reykjavik …, 2009
Megbízások: US National Institutes of Health
Procedure for stability analysis of gene selection from cross-site gene expression data
JN Korecki, LO Hall, D Goldgof, S Eschrich
2011 IEEE International Conference on Systems, Man, and Cybernetics, 909-913, 2011
Megbízások: US National Institutes of Health
Valahol hozzáférhető: 77
Radiomics: the process and the challenges
V Kumar, Y Gu, S Basu, A Berglund, SA Eschrich, MB Schabath, K Forster, ...
Magnetic resonance imaging 30 (9), 1234-1248, 2012
Megbízások: US National Institutes of Health
Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels
M Shafiq‐ul‐Hassan, GG Zhang, K Latifi, G Ullah, DC Hunt, ...
Medical physics 44 (3), 1050-1062, 2017
Megbízások: US National Institutes of Health
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