Fetching the paper…
Reading the bibliography…
Although recent multi-task learning methods have shown to be effective in improving the generalization of deep neural networks, they should be used with caution for safety-critical applications, such as clinical risk prediction.
Multitask learning
Caruana, R. 1997 · 1997
Earlier work this paper cites.
COVID-Net: A tailored deep convolutional neural network design for detection of COVID-19 cases from chest radiography images
Wang, L.; and Wong, A. 2020 · 2003
Earlier work this paper cites.
Relative rates of non-pneumonic SARS coronavirus infection and SARS coronavirus pneumonia
Woo, P. C.; Lau, S. K.; Tsoi, H.-w.; Chan, K.-h.; Wong, B. H.; Che, X.-y.; Tam, V. K.; Tam, S. C.; Cheng, V. C.; Hung, I. F.; et al. 2004 · 2004
Earlier work this paper cites.
Convex multi-task feature learning
Argyriou, A.; Evgeniou, T.; and Pontil, M. 2008 · 2008
Earlier work this paper cites.
Early diagnosis of myocardial infarction with sensitive cardiac troponin assays
Reichlin, T.; Hochholzer, W.; Bassetti, S.; Steuer, S.; Stelzig, C.; Hartwiger, S.; Biedert, S.; Schaub, N.; Buerge, C.; Potocki, M.; et al. 2009 · 2009
Earlier work this paper cites.
MNIST handwritten digit database
LeCun, Y.; and Cortes, C. 2010 · 2010
Earlier work this paper cites.
Learning with Whom to Share in Multi-task Feature Learning
Kang, Z.; Grauman, K.; and Sha, F. 2011 · 2011
Earlier work this paper cites.
PhysioNet 2012 Challenge: Predicting mortality of ICU patients using a cascaded SVM-GLM paradigm
Citi, L.; and Barbieri, R. 2012 · 2012
Earlier work this paper cites.
Learning task grouping and overlap in multi-task learning
Kumar, A.; and Daume III, H. 2012 · 2012
Earlier work this paper cites.
Sparse coding for multitask and transfer learning
Maurer, A.; Pontil, M.; and Romera-Paredes, B. 2013 · 2013
Earlier work this paper cites.
Variations on the MNIST Digits
UdeM. 2014 · 2014
Earlier work this paper cites.
Low resource dependency parsing: Cross-lingual parameter sharing in a neural network parser
Duong, L.; Cohn, T.; Bird, S.; and Cook, P. 2015 · 2015
Earlier work this paper cites.
Retain: An interpretable predictive model for healthcare using reverse time attention mechanism
Choi, E.; Bahadori, M. T.; Sun, J.; Kulas, J.; Schuetz, A.; and Stewart, W. 2016 · 2016
Cited alongside, same era.
Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Gal, Y.; and Ghahramani, Z. 2016 · 2016
Cited alongside, same era.
MIMIC-III, a freely accessible critical care database
Johnson, A. E.; Pollard, T. J.; Shen, L.; Li-wei, H. L.; Feng, M.; Ghassemi, M.; Moody, B.; Szolovits, P.; Celi, L. A.; and Mark, R. G. 2016 · 2016
Cited alongside, same era.
Asymmetric multi-task learning based on task relatedness and loss
Lee, G.; Yang, E.; and Hwang, S. 2016 · 2016
Cited alongside, same era.
Cross-stitch networks for multi-task learning
Misra, I.; Shrivastava, A.; Gupta, A.; and Hebert, M. 2016 · 2016
Cited alongside, same era.
Mortality prediction in the icu based on mimic-ii results from the super icu learner algorithm (sicula) project
Recurrent neural networks for multivariate time series with missing values
Che, Z.; Purushotham, S.; Cho, K.; Sontag, D.; and Liu, Y. 2018 · 2018
Later among the works it cites.
Uncertainty-aware attention for reliable interpretation and prediction
Heo, J.; Lee, H. B.; Kim, S.; Lee, J.; Kim, K. J.; Yang, E.; and Hwang, S. J. 2018 · 2018
Later among the works it cites.
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
Kendall, A.; Gal, Y.; and Cipolla, R. 2018 · 2018
Later among the works it cites.
Attend and diagnose: Clinical time series analysis using attention models
Song, H.; Rajan, D.; Thiagarajan, J. J.; and Spanias, A. 2018 · 2018
Later among the works it cites.
Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19)
Guo, T.; Fan, Y.; Chen, M.; Wu, X.; Zhang, L.; He, T.; Wang, H.; Wan, J.; Wang, X.; and Lu, Z. 2020 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Pirracchio, R. 2016 · 2016
Cited alongside, same era.
Reproducibility in critical care: a mortality prediction case study
Johnson, A. E.; Pollard, T. J.; and Mark, R. G. 2017 · 2017
Cited alongside, same era.
What uncertainties do we need in bayesian deep learning for computer vision?
Kendall, A.; and Gal, Y. 2017 · 2017
Cited alongside, same era.
Deep Asymmetric Multi-task Feature Learning
Lee, H. B.; Yang, E.; and Hwang, S. J. 2017 · 2017
Cited alongside, same era.
Benchmark of deep learning models on large healthcare mimic datasets
Purushotham, S.; Meng, C.; Che, Z.; and Liu, Y. 2017 · 2017
Cited alongside, same era.
Learning what to share between loosely related tasks
Ruder, S.; Bingel, J.; Augenstein, I.; and Søgaard, A. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
Multitask learning and benchmarking with clinical time series data
Harutyunyan, H.; Khachatrian, H.; Kale, D. C.; Ver Steeg, G.; and Galstyan, A. 2019 · 2019
Later among the works it cites.
The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China
Novel, C. P. E. R. E.; et al. 2020 · 2019
Later among the works it cites.
Baricitinib as potential treatment for 2019-nCoV acute respiratory disease
Richardson, P.; Griffin, I.; Tucker, C.; Smith, D.; Oechsle, O.; Phelan, A.; and Stebbing, J. 2020 · 2019
Later among the works it cites.
Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT
Li, L.; Qin, L.; Xu, Z.; Yin, Y.; Wang, X.; Kong, B.; Bai, J.; Lu, Y.; Fang, Z.; Song, Q.; et al. 2020 · 2020
Closest in time.
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
Ma, L.; Gao, J.; Wang, Y.; Zhang, C.; Wang, J.; Ruan, W.; Tang, W.; Gao, X.; and Ma, X. 2020 · 2020
Closest in time.
COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread
McCall, B. 2020 · 2020
Closest in time.
Critical care crisis and some recommendations during the COVID-19 epidemic in China
Xie, J.; Tong, Z.; Guan, X.; Du, B.; Qiu, H.; and Slutsky, A. S. 2020 · 2020
Closest in time.