The final episode of the 4 series webinar on artificial intelligence and machine learning (AI/ML) with the topic: using AI/ML and big data in the context of Real-World Data, Real World Insights and Real-World Evidence for healthcare.

AI/ML, Big Data and RWE are hot topics in today's healthcare discussions. The aim of this webinar session is to move beyond the buzz words and discuss current applications and caveats. Two Dutch healthcare professionals will share their personal experience in working with AI/ML and Big Data in the context of healthcare research. They will share their learnings and ideas from recent and local practical examples.

Agenda

• Introduction – Kirsten Gertsen, Director RWE, HEOR, Market Access & Pricing IQVIA NL
• Predicting a heart attack with machine learning based on medication history – Martijn Otten, PhD Candidate Artificial Intelligence and Resident in the Intensive Care at Amsterdam UMC
  Martijn has worked on predicting a heart attack based on a patient's medication history with the use of machine learning. Why is this relevant? Is it at all possible? And what ingredients are needed to make predictions with machine learning?
• Big Data, Big Responsibility – Aernoud Fiolet, Cardiologist in Training and Researcher at UMC Utrecht
  Introducing big data to regular clinical care and drug research comes with new challenges, encompassing knowledge of the caveats of semi-automatic data collection and prudent use of predictions. In his short lecture, Aernoud provides two typical examples of "technological backfire" and addresses the validity of using clinical trial data via routinely collected data versus dedicated research personnel.