Artificial intelligence-based biomarkers in precision oncology

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Precision oncology requires complex biomarkers which are often based on molecular and genetic tests of tumor tissue. For many of these tests, universal implementation in clinical practice is limited. However, for virtually every cancer patient, pathology tissue slides stained with hematoxylin and eosin (H&E) are available. Artificial intelligence (AI) can extract biomarkers for better treatment decisions from these images. This talk will summarize the state of the art of AI in oncology for precision oncology biomarkers. It will cover the technical foundations, emerging use cases and established applications which are already available for clinical use.

Jakob is a physician scientist with board certification in internal medicine. He was recently appointed professor of Clinical Artificial Intelligence at Technical University Dresden, Germany. His interdisciplinary research team is working at the interface of computer science and precision oncology. The team is guided by an interdisciplinary idea: physicians are trained in data science and researchers from computer science or technical subjects learn to identify and solve clinically relevant problems. In the last year, the team's research studies were published in Nature Medicine and Nature Cancer, among other venues.