Estimating uncertainty and interpretability in deep learning for coronavirus (COVID-19) detection B Ghoshal, A Tucker arXiv preprint arXiv:2003.10769, 2020 | 483 | 2020 |
Consensus clustering and functional interpretation of gene-expression data S Swift, A Tucker, V Vinciotti, N Martin, C Orengo, X Liu, P Kellam Genome biology 5, 1-16, 2004 | 181 | 2004 |
Generating high-fidelity synthetic patient data for assessing machine learning healthcare software A Tucker, Z Wang, Y Rotalinti, P Myles NPJ digital medicine 3 (1), 1-13, 2020 | 156 | 2020 |
Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation M Scutari, C Vitolo, A Tucker Statistics and Computing 29, 1095-1108, 2019 | 117 | 2019 |
Structure and function in glaucoma: the relationship between a functional visual field map and an anatomic retinal map NG Strouthidis, V Vinciotti, AJ Tucker, SK Gardiner, DP Crabb, ... Investigative ophthalmology & visual science 47 (12), 5356-5362, 2006 | 100 | 2006 |
Variable grouping in multivariate time series via correlation A Tucker, S Swift, X Liu IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 31 …, 2001 | 89 | 2001 |
Stochastic dynamic modeling of short gene expression time-series data Z Wang, F Yang, DWC Ho, S Swift, A Tucker, X Liu IEEE transactions on nanobioscience 7 (1), 44-55, 2008 | 84 | 2008 |
A spatio-temporal Bayesian network classifier for understanding visual field deterioration A Tucker, V Vinciotti, X Liu, D Garway-Heath Artificial intelligence in medicine 34 (2), 163-177, 2005 | 78 | 2005 |
Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology N Trifonova, A Kenny, D Maxwell, D Duplisea, J Fernandes, A Tucker Ecological Informatics 30, 142-158, 2015 | 76 | 2015 |
Quantifying StockTwits semantic terms’ trading behavior in financial markets: An effective application of decision tree algorithms A Al Nasseri, A Tucker, S De Cesare Expert systems with applications 42 (23), 9192-9210, 2015 | 75 | 2015 |
Experts integrate explicit contextual priors and environmental information to improve anticipation efficiency. NV Gredin, DT Bishop, DP Broadbent, A Tucker, AM Williams Journal of Experimental Psychology: Applied 24 (4), 509, 2018 | 71 | 2018 |
Modeling air pollution, climate, and health data using Bayesian Networks: A case study of the English regions C Vitolo, M Scutari, M Ghalaieny, A Tucker, A Russell Earth and Space Science 5 (4), 76-88, 2018 | 71 | 2018 |
Evaluation of the early conception factor (ECF™) test for the detection of nonpregnancy in dairy cattle B Gandy, W Tucker, P Ryan, A Williams, A Tucker, A Moore, R Godfrey, ... Theriogenology 56 (4), 637-647, 2001 | 67 | 2001 |
Comparing, contrasting and combining clusters in viral gene expression data P Kellam, X Liu, N Martin, C Orengo, S Swift, A Tucker Proceedings of 6th workshop on intelligent data analysis in medicine and …, 2001 | 63 | 2001 |
Construction of a network describing asparagine metabolism in plants and its application to the identification of genes affecting asparagine metabolism in wheat under drought … TY Curtis, V Bo, A Tucker, NG Halford Food and Energy Security 7 (1), e00126, 2018 | 62 | 2018 |
Estimating uncertainty and interpretability in deep learning for coronavirus (COVID-19) detection. arXiv 2020 B Ghoshal, A Tucker arXiv preprint arXiv:2003.10769, 2003 | 60 | 2003 |
A spatial survey of environmental indicators for Kazakhstan: an examination of current conditions and future needs A Russell, M Ghalaieny, B Gazdiyeva, S Zhumabayeva, A Kurmanbayeva, ... International journal of environmental research 12, 735-748, 2018 | 55 | 2018 |
Literature-based priors for gene regulatory networks E Steele, A Tucker, PAC Hoen, MJ Schuemie Bioinformatics 25 (14), 1768-1774, 2009 | 55 | 2009 |
Rgfga: An efficient representation and crossover for grouping genetic algorithms A Tucker, J Crampton, S Swift Evolutionary Computation 13 (4), 477-499, 2005 | 55 | 2005 |
Estimating uncertainty in deep learning for reporting confidence to clinicians in medical image segmentation and diseases detection B Ghoshal, A Tucker, B Sanghera, W Lup Wong Computational Intelligence 37 (2), 701-734, 2021 | 54 | 2021 |