Deep learning for supervised classification of spatial epidemics

Spatial and Spatio-temporal Epidemiology - Tập 29 - Trang 187-198 - 2019
Carolyn Augusta1, Rob Deardon2, Graham Taylor3
1Department of Mathematics & Statistics, University of Guelph, 50 Stone Rd. E., Guelph, Ontario N1G 2W1 Canada
2Department of Mathematics & Statistics and Department of Production Animal Health, University of Calgary, Calgary, Alberta T2N 1N4 Canada
3School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, Ontario N1G 2W1, Canada

Tài liệu tham khảo

Bergstra, 2012, Random search for hyper-parameter optimization, J Mach Learn Res, 13, 281 Bifolchi, 2013, Spatial approximations of network-based individual level infectious disease models, Spat Spatio-Temporal Epidemiol, 6, 59, 10.1016/j.sste.2013.07.001 Breiman, 2001, Random forests, Mach Learn, 45, 5, 10.1023/A:1010933404324 Burdett, 2015, Simulating the distribution of individual livestock farms and their populations in the United States: an example using domestic swine (Sus scrofa domesticus) farms, PloS One, 10, e0140338, 10.1371/journal.pone.0140338 Chollet F. Keras. https://github.com/fchollet/keras; 2015. Cui, 2004, A study of sample size with neural network, 6, 3444 Deardon, 2010, Inference for individual-level models of infectious diseases in large populations, Stat Sin, 20, 239 Deardon, 2014, Statistical modelling of spatio-temporal infectious disease transmission, 211 Dietz, 1988, The first epidemic model: a historical note on PD En’ko, Aust N Z J Stat, 30, 56, 10.1111/j.1467-842X.1988.tb00464.x Dietz, 2002, Daniel Bernoulli’s epidemiological model revisited, Math Biosci, 180, 1, 10.1016/S0025-5564(02)00122-0 Gani, 1969, A chain binomial study of inoculation in epidemics, Bull ISI, 43, 203 Gani, 2001, Pyotr dimitrievich En’ko, 223 Gani, 1971, Markov chain methods in chain binomial epidemic models, Biometrics, 27, 591, 10.2307/2528598 Goodfellow, 2016 Günther, 2010, Neuralnet: training of neural networks, R J, 2, 30, 10.32614/RJ-2010-006 Keeling, 2001, Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape, Science, 294, 813, 10.1126/science.1065973 Kermack, 1927, A contribution to the mathematical theory of epidemics, 115, 700 Lessler, 2016, Mechanistic models of infectious disease and their impact on public health, Am J Epidemiol, 183, 415, 10.1093/aje/kww021 Liaw, 2002, Classification and regression by randomForest, R News, 2, 18 Nsoesie, 2011, Prediction of an epidemic curve: a supervised classification approach, Stat Commun Infect. Dis, 3 Pedregosa, 2011, Scikit-learn: machine learning in python, J Mach Learn Res, 12, 2825 Pokharel, 2014, Supervised learning and prediction of spatial epidemics, Spat Spatio-Temporal Epidemiol, 11, 59, 10.1016/j.sste.2014.08.003 Quast, 2016, rnn: a Recurrent Neural Network in R, Working Papers Rajkumar, 2003, Training data requirement for a neural network to predict aerodynamic coefficients Riley, 2003, Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions, Science, 300, 1961, 10.1126/science.1086478 Singh, 2017, Scatternet hybrid deep learning (SHDL) network for object classification Suzuki, 2003, Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT, 1355 Wang, 2017, Time series classification from scratch with deep neural networks: a strong baseline, 1578