In intensive care, various devices continuously assess the patient status providing a large amount of data. Medical practitioners must act on such data, most often under time constraints and roughly being able to oversee the huge amounts of information and interconnections. Artificial intelligence (AI) provides the opportunity to tackle this huge amount of data, reducing the burden on the medical staff and allowing not only to react adequately on the current situation but foresee acute events enabling preventive care. Despite a huge potential, many challenges prevent a wide adoption of AI in clinical practice. Algorithms do not yet perform with sufficient precision in many cases. Automated algorithms also need to provide insights on their decision making to facilitate acceptance/trust by clinicians and patients.

At DSENS, we work on multiple aspects regarding the usage of physiological time series or other patient data to improve patient monitoring, better identify patients at risk of adverse events and optimize individual care. Projects are ranging from basic to applied research projects involving clinicians and industrial partners.