Welcome! Please contribute your ideas for what challenges we might aspire to solve, changes in our community that can improve machine learning impact, and examples of machine learning projects that have had tangible impact.
Lacking context for this site? Read the original paper: Machine Learning that Matters (ICML 2012). You can also review the slides.
Predicting successful drug combinations for HIV therapy
  • Our lab uses machine learning to predict an optimal therapy for HIV patients, based on the viral genotype. This is a tricky problem, with numerous possible medications with different modes of action which must be combined while considering the current and future viral resistance profile. We do it using support vector machines

    Our software has become standard of care in Germany.

    We are extending to HBV and HCV.

    See our homepage for more info, including relevant publications.


To post or add a comment, please sign in or register.


Tip: click the star icon to bookmark (follow) a discussion. You will receive email notifications of subsequent activity.
If search doesn't work, try putting a + in front of your search term.