AI in Healthcare

In recent years, the volume of healthcare data has exploded, both through patient-generated data through wearables and clinical data. Advanced clinical diagnostic and treatment methods in all fields, from radiology to pathology and molecular biology, produce vast amounts of structured and unstructured data and have further increased the need to analyse them.

AI is seen as a promising approach that enables the automated analysis of large amounts of data from various medical fields. The following webinar will help us to understand what the current state of the art of AI in healthcare is and will bring together scholars who report on their daily work with AI. What are the opportunities offered by this much talked about yet poorly understood technology? Whatare the risks? What needs to be done to make the most of the potential? These and other questions will be discussed together with an interdisciplinary audience.

Panelists

Leo Anthony Celi (Principal Research Scientist, Massachusetts Institute of Technology,
Clinical Research Director, Laboratory of Computational Physiology)
Sandy Engelhardt (Head of Working Group ‘Artificial Intelligence in Cardiovascular
Medicine’, University Hospital Heidelberg)
Liebet Geris (Research Professor in Biomechanics and Computational Tissue Engineering,
University of Liège, KU Leuven)

Literatur

[1] Magrabi et al. (2020): Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications, DOI: 10.1055/s-0039-1677903

[2] Topol et al. (2019): High-performance medicine: the convergence of human and artificial intelligence, DOI: 10.1038/s41591-018-0300-7