The breadth of AI in healthcare applications is broad. How much human oversight is necessary or preferred when leveraging AI in the interest of patient safety? 
Listen to this in-depth discussion on how AI can help identify end-to-end data weaknesses, as well as broader implications regarding the inevitability of human interaction.
This is part two of a discussion focused upon data bias, accuracy, access and the future of AI in drug development. 
 
Host 
<a href="https://www.linkedin.com/in/lorielliskatz/">⁠Lori Ellis⁠</a>, Head of Insights, BioSpace  
 
Guests 
<a href="https://www.linkedin.com/in/paul-agapow/">⁠Paul Agapow⁠</a>, Director of Innovation, Data Science and Strategy, GlaxoSmithKline<a href="https://www.linkedin.com/in/michaeljking/">⁠</a>
<a href="https://www.linkedin.com/in/michaeljking/">Mike King⁠</a>, Senior Director of Product and Strategy, IQVIA 
<a href="https://www.linkedin.com/in/nindhanaparanthaman/">⁠Nindhana Paranthaman⁠</a>, Executive Medical Director, Exelixis 
<a href="https://www.linkedin.com/in/movosto/">⁠Moritz von Stosch⁠</a>, Chief Information Officer, DataHow

Artificial Intelligence, Part 3: Improving Communication to Impact Patient Behavior

Unravel the business of science with BioSpace. We dive into biopharma's top stories and biggest challenges, whether it’s layoffs, pipeline shake-ups, acquisitions, new FDA approvals or how to regulate AI in drug development.