Talking Precision Medicine

The latest episode of Talking Precision Medicine podcast, our own Gabe Muso, speaks with Rafael Rosengarten CEO of Genialis on the practice of improving data preprocessing for the advancement of machine learning in medicine.

Episode highlights:

  • Drug discovery is an expensive endeavor. So how can we use machine learning effectively to reduce the costs in terms of generating better early clinical leads, better understanding and partitioning patients into disease categories and definitions, and then ultimately how do we understand the full consequence of each of those diseases and diagnosis
  • When you look at why machine learning will tend to fail, it’s not an algorithmic problem, the algorithms are sufficiently advanced, it’s a data problem. So how can we improve that data processing or have more transparency over that data process so we can refine it a little bit more easily and quickly
  • The blessing curse of the machine learning is that it doesn’t care what inputs you give it, it will always try to run the algorithm and give you the result.
  • Data are the new currency, this is what builds value, not only for companies but for anybody.
  • Toronto is a hot bed of biomedical machine learning
  • Announcement of new Augusta™ launch