Joseph Kvedar

Hear from Stanford professor Nigam Shah about the practical considerations and evaluation challenges of implementing artificial intelligence into clinical practice.

Learn about significant challenges concerning data privacy and governance affecting medical AI.

Hear from a leading thought leader on medical innovation.

Hear from one of the leading researchers and public voices in digital medicine.

Hear about the future of digital health from former FDA Commissioner Robert Califf.

In this inaugural episode of The Digital Pulse, the official podcast of npj Digital Medicine, we sit down with the journal’s Editor-in-Chief for an in-depth conversation exploring the evolving landscape of digital health, artificial intelligence, and the future of medicine. As digital technologies increasingly shape how healthcare is delivered, evaluated, and experienced, this discussion offers a rare behind-the-scenes perspective on how leading scientific journals are guiding innovation responsibly. The Editor-in-Chief, Dr. Joseph Kvedar, reflects on the journal’s mission, and listeners gain insight into emerging research priorities shaping the field today. Dr. Kvedar will share practical tips for getting your research published and discuss the different content formats available for authors looking to contribute to the journal. Whether you are an early-career researcher, clinician, or digital health innovator, this conversation offers valuable insight into navigating scientific publishing in the era of digital medicine.

Generative AI is designed to create new content from trained parameters. Learning from large amounts of data, many of these models aim to simulate human conversation. Generative AI is being applied to many different sectors. Within healthcare there has been innovation specifically towards generative AI models trained on electronic medical record data. A recent review characterizes these models, their strengths, and weaknesses. Inspired by that work, we present our evaluation checklist for generative AI models applied to electronic medical records.