ML-AIM Machine Learning and Artificial Intelligence for Medicine

Research Laboratory led by Prof. Mihaela van der Schaar

    Early warning systems

  1. J. Yoon, W. R. Zame and M. van der Schaar, "Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks," IEEE Transactions on Biomedical Engineering, 2018. [Link]
  2. J. Yoon, W. R. Zame, M. van der Schaar, "Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks," ICLR, 2018. [Link]
  3. Q. Feng, J. Yoon, M. van der Schaar, "ACW-RNN: Adaptive Clockwork Recurrent Neural Networks for Early Warning Systems in Hospitals," AI Med Europe Abstract Competition, 2018. [Link]
  4. A. Alaa and M. van der Schaar, "A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference," Journal of Machine Learning Research (JMLR), 2017. [Link]
  5. A. Alaa, J. Yoon, S. Hu and M. van der Schaar, "Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes," IEEE Transactions on Biomedical Engineering, 2017. [Link]
  6. A. M. Alaa, S. Hu, and M. van der Schaar, "Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis," ICML, 2017. [Link]
  7. A. M. Alaa, J. Yoon, S. Hu, M. van der Schaar, "A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data," NIPS - Workshop on Machine Learning for Health, 2016. [Link]
  8. A. M. Alaa, J. Yoon, S. Hu, M. van der Schaar, "Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts," ICML 2016 - Workshop on Computational Frameworks for Personalization., 2016. [Link]
  9. J. Yoon, A. M. Alaa, S. Hu, M. van der Schaar, "ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission," ICML 2016. [Link]