AI, Machine Learning and Big Data for Life Sciences: The Good, the Bad and the Ugly

Thursday, November 15, 3:50 - 4:30 PM

Speaker(s): Matthew Clark, PhD

Room #: Madison

Artificial Intelligence (AI) has the potential to revolutionize life sciences and healthcare. The movement started with Alan Turing in 1950, “Can a machine imitate human intelligence?” and progressed in the late 1970s to solving rudimentary problems. More recently there has been a great increase in applying Machine Learning and Natural Language Processing techniques across the sciences—from early preclinical drug discovery to selecting precision treatments for individual patients.

Recent reports of large life science AI initiatives failing to deliver on expectations demonstrate that there are significant pitfalls in the application of AI and Big Data—challenges that can be overcome with better normalizing of vocabularies and mining from multiple data sources. And there have also been success stories in life sciences, like those with Google and pathology. 

This presentation will offer an insightful overview of best and worst practices in applying AI and Machine Learning to life sciences to facilitate the successful use of these techniques in today’s competitive drug discovery environment.

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