Knowledge graphs are a critical backbone for data-driven decision-making, while generative AI can transform personalized patient care, expedite drug discovery, enhance medical imaging, and even revolutionize robot-assisted surgery. Together, they’re a powerful combination.

To explore how these two technologies are reshaping the healthcare landscape, join this 45-minute session. We’ll discuss:

  • The groundbreaking capabilities of accurate GenAI in healthcare
  • The challenges with integrating AI into medicine
  • Practical medical applications for knowledge graphs
  • How healthcare professionals are using tools like ChatGPT for effective patient care  
  • The process of creating life sciences-focused knowledge graphs with Neo4j
Don’t miss this opportunity to discover the next frontier in state-of-the-art healthcare. 

Dr. Alexander Jarasch
Field Engineer, Neo4j

With a background in bioinformatics, Alexander Jarasch obtained his Ph.D. in biochemistry and structural bioinformatics at the Gene Center Munich (LMU). As a postdoctoral fellow, on behalf of Evonik Industries AG, he developed protein engineering software for 3D modeling of enzyme candidates with biotech application. As part of the Global Strategic Team at Roche Diagnostics GmbH he developed machine learning techniques for predicting more chemically stable antibodies. From March 2017 through 2022, he was head of data and knowledge management at The German Center for Diabetes Research (DZD), where he was responsible for a knowledge graph database and machine learning techniques in diabetes research. He joined Neo4j in 2022 as a field engineer.

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