[22]
Matheny, M.E.; Thadaney, I.S.; Ahmed, M.; Whicher, D. Artificial intelligence in health care: A report from the national academy of medicine. JAMA, 2020, 323(6), 509-510.
[36]
Goodfellow, I.; Bengio, Y.; Courville, A. Deep Learning; MIT Press: London, England, 2016.
[40]
Wu, Y.; Schuster, M.; Chen, Z.; Le, Q.V.; Norouzi, M.; Macherey, W.; Krikun, M.; Cao, Y.; Gao, Q.; Macherey, K.; Klingner, J.; Shah, A.; Johnson, M.; Liu, X; Kaiser, Ł.; Gouws, S.; Kato, Y.; Kudo, T.; Kazawa, H.; Stevens, K.; Kurian, G.; Patil, N.; Wang, W.; Young, C.; Smith, J.; Riesa, J.; Rudnick, A.; Vinyals, O.; Corrado, G.; Hughes, M.; Dean, J. Google’s neural machine translation system: Bridging the gap between human and machine translation. arXiv:1609.08144, 2016.
[57]
Da Silva, I.N.; Spatti, H.; Flauzino, A.; Liboni, R.; Dos Reis Alves, L.; Da Silva, S.F. Artificial Neural Network Architectures and Training Processes. Artif. Neural Networks; Springer International Publishing: NY City, 2017.
[70]
Chabon, J.J.; Hamilton, E.G.; Kurtz, D.M.; Esfahani, M.S.; Moding, E.J.; Stehr, H.; Schroers-Martin, J.; Nabet, B.Y.; Chen, B.; Chaudhuri, A.A.; Liu, C.L.; Hui, A.B.; Jin, M.C.; Azad, T.D.; Almanza, D.; Jeon, Y.J.; Nesselbush, M.C. Co Ting Keh, L.; Bonilla, R.F.; Yoo, C.H.; Ko, R.B.; Chen, E.L.; Merriott, D.J.; Massion, P.P.; Mansfield, A.S.; Jen, J.; Ren, H.Z.; Lin, S.H.; Costantino, C.L.; Burr, R.; Tibshirani, R.; Gambhir, S.S.; Berry, G.J.; Jensen, K.C.; West, R.B.; Neal, J.W.; Wakelee, H.A.; Loo, B.W., Jr; Kunder, C.A.; Leung, A.N.; Lui, N.S.; Berry, M.F.; Shrager, J.B.; Nair, V.S.; Haber, D.A.; Sequist, L.V.; Alizadeh, A.A.; Diehn, M. Integrating genomic features for non-invasive early lung cancer detection.
Nature, 2020,
580(7802), 245-251.
[
http://dx.doi.org/10.1038/s41586-020-2140-0] [PMID:
32269342]
[88]
Yang, Y.; Sun, J.; Li, H.; Xu, Z ADMM-Net: A deep learning approach for compressive sensing MRI arXiv:1705.06869, 2017.
[93]
Le Cun, Y.; Jackel, L.D.; Boser, B.; Denker, J.S.; Graf, H.P.; Guyon, I.; Henderson, D.; Howard, R.E.; Hubbard, W. Handwritten digit recognition: applications of neural network chips and automatic learning. IEEE Commun. Mag., 1990, 27(11), 41-46.
[101]
Y., Bengio; P., Lamblin; D., Popovici; H., Larochelle; U., Montreal Greedy Layer-Wise Training of Deep Networks In: Advances in Neural Information Processing Systems; The MIT Press: Massachusetts, 2007.
[102]
Erhan, D.; Courville, A.; Bengio, Y.; Vincent, P. Why does unsupervised pre-training help deep learning? J. Mach. Learn. Res., 2010, 11, 201-208.
[104]
Srivastava, N.; Hinton, G.; Krizhevsky, A.; Sutskever, I.; Salakhutdinov, R. Dropout: A simple way to prevent neural networks from overfitting. J. Mach. Learn. Res., 2014, 15, 1929-1958.
[105]
Ioffe, S.; Szegedy, C Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv:1502.03167, 2015.
[113]
Wallach, I.; Dzamba, M.; Heifets, A AtomNet: A deep convolutional neural network for bioactivity prediction in structure-based drug discovery. arXiv:1510.02855, 2015.
