ML-AIM Machine Learning and Artificial Intelligence for Medicine

Research Laboratory led by Prof. Mihaela van der Schaar

    Medical imaging


  1. T. Kyono, F. J. Gilbert, M. van der Schaar, "Multi-view Multi-task Learning for Improving Autonomous Mammogram Diagnosis," Machine Learning for Healthcare Conference (MLHC), 2019. [Link]
  2. T. Kyono, F. J. Gilbert, M. van der Schaar, "Improving Workflow Efficiency for Mammography Using Machine Learning," Journal of the American College of Radiology, 2019. [Link]
  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," 2018. [Link]
  4. A. M. Alaa, F. J. Gilbert, Y. Huang, M. van der Schaar, "Machine Learning for Identifying the Value of Digital Breast Tomosynthesis using Data from a Multicentre Retrospective Study," Radiological Society of North America (RSNA), 2018. [Link] [Presentation]
  5. 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]
  6. L. Song, W. Hsu, J. Xu and M. van der Schaar, "Using contextual learning to improve diagnostic accuracy: application in breast cancer screening," IEEE J. Biomedical and Health Informatics, 2015. [Link]
  7. C. Tekin and M. van der Schaar, "Active Learning in Context-Driven Stream Mining with an Application to Image Mining," IEEE Trans. Image Process., vol. 24, no. 11, 2015. [Link]