Abstract:
Hey techies! I’m so pumped to share our story with you all today about building a scalable data platform that’s a real accelerator for AI use cases in the medical sector. My team and I took on this challenge from the ground up, using Azure as our go-to platform, and I can’t wait to share what we learned. You’ll hear all about the approaches that worked for us, but also the pitfalls we encountered along the way. I’ll be taking you on a journey filled with technical knowledge, real-world experiences, and a whole lot of enthusiasm. So, buckle up and get ready for a 20-minute ride filled with insights and inspiration.

Bio:
I was born in Vietnam living in a poor neighborhood, came to Germany when I was 12 years old, fought my way through teenage years with full of pain, racism and prejudice to start my own 7 figure business in AI and Cloud 16 years later. Now I am the founder and CEO of Datics, a fully remote technology service company focusing on Cloud / DevOps / AI. I have a software development background and love to generate knowledge out of huge amount of data

Abstract:
Sepsis (blood poisoning) is a life-threatening condition which is as serious as a heart attack and needs immediate attention. This talk will be about how we use ML to predict the onset of sepsis. We will address the anatomy of the disease, discuss current research and touch on the challenges when predicting such a complex disease. Also, we will look into the special requirements in healthcare and its implications for model development.

Bio:
Dang-Khoa is a data scientist and medical doctor from Berlin. Currently, he is conducting research in Machine Learning & Medicine for his doctoral thesis at Charité. Dang-Khoa is passionate about advancing patient care and medical treatments using ML.