cc The ML-AIM Group

ML-AIM Machine Learning and Artificial Intelligence for Medicine

Research Laboratory led by Prof. Mihaela van der Schaar

Risk & Prognosis

Autoprognosis

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Cystic Fibrosis

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  • C. Lee, J. Yoon, M. van der Schaar, "Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis with Competing Risks based on Longitudinal Data," IEEE Transactions on Biomedical Engineering (TBME), 2019. [Link]
  • C. Lee, W. R. Zame, A. M. Alaa, M. van der Schaar, "Temporal Quilting for Survival Analysis," International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. [Link] [Supplementary Materials]
  • A. Bellot, M. van der Schaar, "Boosting Survival Predictions with Auxiliary Data from Heterogeneous Domains," International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. [Link]
  • A. M. Alaa, T. Bolton, E. Di Angelantonio, J. H. F. Rudd, M. van der Schaar, "Cardiovascular Disease Risk Prediction using Automated Machine Learning: A Prospective Study of 423,604 UK Biobank Participants," PloS One, 2019.
  • A. M. Alaa, M. van der Schaar, "Prognostication and Risk Factors for Cystic Fibrosis via Automated Machine Learning," Scientific Reports, 2018. [Link]
  • C. Rietschel, J. Yoon, and M. van der Schaar, "Feature Selection for Survival Analysis with Competing Risks using Deep Learning," NIPS Machine Learning for Health Workshop 2018. [Link]
  • J. Yoon, W. R. Zame, A. Banerjee, M. Cadeiras, A. Alaa, M. van der Schaar, "Personalized survival predictions via Trees of Predictors: An application to cardiac transplantation," PloS One, 2018. [Link] [Calculator Link]
  • J. Yoon, W. R. Zame, M. van der Schaar, "ToPs: Ensemble Learning with Trees of Predictors," IEEE Transactions on Signal Processing (TSP), 2018. [Link]
  • A. Bellot, M. van der Schaar, "Boosted Trees for Risk Prognosis," Machine Learning for Healthcare Conference (MLHC), 2018. [Link]
  • A. M. Alaa, M. van der Schaar, "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning," ICML, 2018. [Link] [Webpage]
  • A. Bellot, M. van der Schaar, "Multitask Boosting for Survival Analysis with Competing Risks," NIPS, 2018.
  • [Link]
  • B. Lim, M. van der Schaar, "Disease-Atlas: Navigating Disease Trajectories using Deep Learning," Machine Learning for Healthcare Conference (MLHC), 2018. [Link] [Presentation] - Best Paper Award in IJCAI-BOOM Workshop
  • C. Lee, W. R. Zame, J. Yoon, M. van der Schaar, "DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks," AAAI, 2018. [Link] [Supplementary Materials]
  • A. Bellot, M. van der Schaar, "A Hierarchical Bayesian Model for Personalized Survival Predictions," IEEE J. Biomedical and Health Informatics, 2018. [Link] [Supplementary Materials]
  • A. Bellot, M. van der Schaar, "Tree-based Bayesian Mixture Model for Competing Risks," AISTATS, 2018. [Link]
  • A. M. Alaa, M. van der Schaar, "Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks," NIPS, 2017. [Link] - Selected as a spotlight paper