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Big Data has transformed the way that business is conducted in recent years, from Internet-based startups to blue chip standbys such as IBM and Wal-mart. However, many of the machine learning tools that have enabled this...
Machine Learning in Biomedical Research with Justin Mower is an episode from Unconventional Computing by Rice University Computer Science. Big Data has transformed the way that business is conducted in recent years, from Internet-based star...
This episode belongs to Unconventional Computing.
Use the player on this page to stream the episode online.
Published Jan 8, 2019, 32:00 long, audio available.
Big Data has transformed the way that business is conducted in recent years, from Internet-based startups to blue chip standbys such as IBM and Wal-mart. However, many of the machine learning tools that have enabled this transformation are not capable of solving complex biomedical problems, which often have their own sophisticated vocabulary and data standards. In today's podcast, we'll learn about research at Rice which seeks to use task-specific machine learning to assist biomedical researchers in discovering and verifying drug interactions.
You can listen to Machine Learning in Biomedical Research with Justin Mower online on Radio and Podcast. Open the player on this page to stream the available audio.
Machine Learning in Biomedical Research with Justin Mower is an episode from Unconventional Computing by Rice University Computer Science.
This episode is 32:00 long.
This episode was published on Jan 8, 2019.
Yes. Use the heart button on the episode page to add it to your favorite episodes list.
Yes. This page shows related episodes from Unconventional Computing when more episodes are available from the podcast feed.
You can listen to Machine Learning in Biomedical Research with Justin Mower on this page when the episode audio is available from the podcast feed.
Machine Learning in Biomedical Research with Justin Mower is from Unconventional Computing by Rice University Computer Science.
Published Jan 8, 2019 and 32:00 long