Programpunkter

Insights from work in the cardiovascular ML lab at Stanford University, including deep learning ECGs, analyzing data from wearable devices and application of large language models.

Leveraging high-resolution 3D printing, we are redefining how treatments are administered, enhancing patient comfort, and driving better health outcomes. Our innovative microneedle array platform integrates real-time biomarker monitoring with controlled drug delivery, transforming disease prevention, treatment, and personalized medicine. By replacing traditional blood draws with painless, minimally invasive, and cost-effective 3D-printed microneedle patches, we enable biomarker sampling from interstitial fluid (ISF)—a rich source of molecular information comparable to blood. Beyond diagnostics, this microarray platform enables targeted, needle-free delivery of vaccines and therapeutics into the intradermal space, offering a scalable and adaptable approach to vaccination and treatments. Our goal is to advance precision health by making continuous monitoring and proactive care more accessible, beyond a hospital setting.

AI is powerful tool for discovering new facts about the world, many too subtle for human eyes. I’ll give a few emerging examples of how AI-driven insights can help doctors treat patients better, and give researchers new puzzles to crack. This human–AI loop will create a new science of medicine, powered by data and computation, as well as enormous economic value.

The Bay Area around San Francisco has two world-class universities and hospitals in precision health and AI, as well as many start-ups and several of the largest tech companies in health. How does research in AI in precision health translate to an impact for patient health in the Bay Area? What can Sweden learn from success stories (and failures) of bringing safe and responsible AI in precision health to good use for patients?

Sweden and Silicon Valley are two of the most innovative place in the world and both have a strong focus on applied AI. But how can better connect the two ecosystems of applied AI in precision health, collaborate and learn from each other?

Handling of health data for AI in the US and Europe vary vastly. What are the different approaches and how does that effect healthcare and the patient?

The California/US way of supporting innovation and research contra Sweden? What are the differences and what could be the better way? How do we ensure scientific quality of AI in precisions health? Whose responsibility is it to make sure that all infrastructure is in place and that we are working long term not with projects only?