Explore AI in Pharma – at the Intelligent Health Summit
AI is now first in line in the minds of healthcare leaders driving transformation. But all the exciting opportunities come hand in hand with some tough challenges and questions. A lack of implementation expertise, or how to ensure efficiency, reliability and the privacy of health data comes to mind. We have a lot of ideas on how to solve these challenges.
Like federated learning – a concept, that could break open data silos without risking privacy. At this year’s Intelligent Health Summit we will present its opportunities and limitations. We would love to discuss with you how your company can benefit from it.
Intelligent Health Summit #onlineedition
September 9th - 10th 2020
Intelligent Health is the only large-scale, global summit series focused purely on AI in healthcare. This is the place where industry-leading speakers set the AI agenda in healthcare for 2020 and beyond. They will talk about how to solve all those small and big challenges that come along with it – from the implementation in the company, the cultural changes to leading lighthouse projects to success.
We are proud that Zühlke and the AO Foundation are the only participants at the Intelligent Health Summit presenting the topic of federated learning. We believe that this concept can combine more data with more data privacy. This is a golden opportunity for pharma companies – and we would like to discuss with you how you can take it.
Our Involvement
AI in pharma has achieved significant successes in recent years and has gained traction in clinical adoption. But AI comes with some big challenges – data privacy being one of the larger ones. Our five principles on applying AI in Pharma and Life Science will cover most of these risks. But wouldn’t it be neat if there was a way to break up data silos by letting ML models travel to these silos and come back better and smarter – but without patient data? That is what federated learning is about.
In our presentation at the Intelligent Health Summit we highlight the motivation and benefits of a federated learning platform, its architecture, as well as organizational and legal aspects of federated machine learning in a regulated field. We further present experimental results for semantic segmentation of computed tomography (CT) scans of vertebrae in a differentially private federated learning setting.
Our speakers will give an insight into this topic on September 9th at 1.40 pm to 2 pm and are looking forward to an interactive exchange with you.
Our presentation Privacy preserving federated learning for AI in healthcare with an application to semantic segmentation of computed tomography (CT) scans of vertebrae will be held by
- Dr. Gabriel Krummenacher, Team Lead Data Science Zühlke Group
- Tomas Dikk, Lead Data Science Zühlke Group
- Roland Herzog, Head Technology Transfer, AO Foundation
In addition to our talk we are hosting further sessions on each day:
- Boris Langer: Jumping the innovation chasm - from AI-lab to diagnostics product in 6 months
- Gian-Marco Baschera: The Anatomy of Data-Driven Companies
When it comes to the implementation of AI in pharma and methods like federated learning, every company and even every department is unique. That’s why we would like to hear from you: What are your challenges? What are your goals? And how would you like to achieve them?
Why we are the right partner
At Zühlke, we are happy to help you develop medical grade data algorithms, connect you with patients and gain their trust, realize medical grade devices, build digital health platforms and accelerate the time to market of your products.
|
|
|
|
|
|
|
|
|