Medical, health, and genomics
Video
Episode 3: Collaborating faster
Healthcare innovation is moving more quickly than ever from research to real-world applications. This episode explores the accelerated research cycles and sharing of information and feedback that drives faster technology incubation, finetuning and scaling. This…
Video
Episode 2: A multi-disciplinary approach
In this episode, the team explores the value of including different perspectives when addressing a complex challenge. They reflect on lessons learned: innovation works best when everyone has a seat at the table. By combining…
Video
Episode 1: Tackling complex healthcare challenges
In this episode, Microsoft Research and Microsoft Health and Life Sciences leaders reflect on how AI is beginning to ease real-world challenges in healthcare. From reducing the burden of clinical documentation to improving data access…
Podcast
What AI’s impact on individuals means for the health workforce and industry
Ethan Mollick and Azeem Azhar, thought leaders at the forefront of AI’s influence on work, education, and society, discuss the impact of AI at the individual level and what that means for the healthcare workforce…
Podcast
Collaborators: Healthcare Innovation to Impact
In this discussion, Matthew Lungren, Jonathan Carlson, Smitha Saligrama, Will Guyman, and Cameron Runde explore how teams across Microsoft are working together to generate advanced AI capabilities and solutions for developers and clinicians around the…
Podcast
Coauthor roundtable: Reflecting on real world of doctors, developers, patients, and policymakers
Peter Lee and his coauthors, Carey Goldberg and Dr. Zak Kohane, reflect on how generative AI is unfolding in real-world healthcare, drawing on earlier guest conversations to examine what’s working, what’s not, and what questions…
Podcast
Laws, norms, and ethics for AI in health
Healthcare experts Laura Adams, Vardit Ravitsky, and Dr. Roxana Daneshjou discuss responsible AI implementation in medicine, examining governance approaches, shifting patient-provider relationships, and the identification of bias to ensure equitable deployment.
