Machine learning algorithms can be trained to distinguish wolves from dogs in photographs, but sometimes these algorithms learn incorrectly by assuming that any animal pictured with snow in the background is a wolf (bottom right). Two School scientists argue that scientific applications of machine learning also need to be monitored to ensure they are working properly.
Michael Keiser, PhD, and Kangway Chuang, PhD, want to use machine learning to speed the pace of drug discovery. By digging into the work of another lab, the pair realized how machine learning could lead scientists astray—and came up with methods to avoid its worst pitfalls.
Michael Keiser, PhD, received a Ben Barres Early Career Acceleration Award from the Chan Zuckerberg Initiative, which will support his research into novel therapies for neurodegeneration.
Michael Keiser, PhD, received a Ben Barres Early Career Acceleration Award from the Chan Zuckerberg Initiative, which will fund his research into novel therapies for neurodegeneration.
A new PharmD curriculum; Implementing new practice opportunities for pharmacists; PharmD students shine in state and national clinical pharmacy competitions; A pioneer in pharmacogenomics; The NIH streak lives on; Improving adverse event reporting and medication therapy protocols; Big-data to cut...
A supercomputer in the Lawrence Livermore National Laboratory will be used in Project ATOM, a new public-private project that aims to speed discovery of new drug therapies.
A pioneering public/private consortium is poised to turn the marathon of drug discovery into a team relay, maybe even a short one.
