ML-AIM Machine Learning and Artificial Intelligence for Medicine

Research Laboratory led by Prof. Mihaela van der Schaar

    Screening

  1. 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
  2. D. Jarrett, J. Yoon, and M. van der Schaar, "MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks," NIPS Machine Learning for Health Workshop 2018. - Selected as spotlight talk [Link] [Poster]
  3. T. Kyono, F. J. Gilbert, and M. van der Schaar, "MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine Collaboration in Breast Cancer Diagnosis," Submitted, 2018. [Link]
  4. 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]
  5. J. Yoon, W. R. Zame, M. van der Schaar, "Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks," ICLR, 2018. [Link]
  6. K. Ahuja, W. R. Zame, M. van der Schaar, "DPSCREEN: Dynamic Personalized Screening," NIPS, 2017. [Link][Poster]
  7. A. Alaa, K. H. Moon, W. Hsu and M. van der Schaar, "ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening," IEEE Transactions on Multimedia - Special Issue on Multimedia-based Healthcare, 2016. [Link]