Our speakers
Big Data and AI in Biomedicine
Pieter Kubben
Opening lecture on big data & AI
As a leading neurosurgeon at Maastricht UMC+, Dr. Kubben brings a wealth of expertise in cutting-edge research areas such as adaptive deep brain stimulation and brain-computer interfacing. His pivotal role in establishing the eHealth program at MUMC+ underscores his commitment to leveraging technology for healthcare advancement.
As the opening keynote speaker, Dr. Kubben will illuminate critical concepts of big data and AI, equipping the audience with essential background knowledge as they explore the subject further in the following presentations. Don't miss this opportunity to gain essential insights from a visionary in the field of neurosurgery and data science!
Rianne Fijten
Shared-decision making in cancer
Rianne Fijten, Assistant Professor at Maastricht University and Maastro, is at the forefront of Clinical Data Science, leveraging AI to enhance patient outcomes in medical decision-making. With a background rooted in biomedical sciences, Dr. Fijten's journey into data science began during her Master's and PhD studies. Here, she performed research on the diagnosis of diseases (including cancer) using the exhaled breath of patients.
During her presentation, Dr. Fijten will highlight a variety of clinical cases in which AI can make a difference. In particular, she will focus on AI that supports decision-making by predicting future events such as cancer survival and recurrence or side effects of treatment.
Liesbet Peeters
Real-world data
Liesbet M. Peeters is an assistant professor, leading the research group of biomedical data sciences at Hasselt University (Belgium). This research group is affiliated with both the Biomedical Research Institute as well as the Data Science Institute. They are a multidisciplinary team that consists of researchers with a (bio)medical background as well as with a data science background (and everything in between). Together, they make the connections between the two very different worlds of biomedical sciences and data sciences.
In her lecture, Liesbet will inspire the audience about how #DataSavesLives and how biomedical researchers can contribute to the wicked problem of health data sharing and use. Don't miss this opportunity to gain insights from a leader at the forefront of health data transformation. See you at MOSA Conference 2024!
Mehrdad Seirafi
Application of AI in neurological research
Mehrdad Seirafi, a neurotech entrepreneur based in Maastricht, holds a PhD in cognitive neuroscience from Maastricht University, where he originally studied physics. Alongside being the co-founder, he serves as the tech lead at Alpha Brain Technologies, a deep-tech medical device company.
During his lecture, Dr. Seirafi will shed light on NEVOA-AI, an embedded-AI for continuous monitoring of the brain in real time developed by Alpha Brain Technologies. This AI is able to predict and potentially prevent brain-related catastrophes, such as epileptic seizures, before happening.
William Van Doorn & Paul Van Dam
Machine learning for risk stratification in the emergency department
William Van Doorn, a resident in clinical chemistry, and Paul van Dam, an internist in acute medicine, are both working at Maastricht UMC+ and leading researchers of the MARS-ED trial. During their talk, they will introduce the audience to the MARS-ED trial and the use of AI tools to help decision-making for patient care.
Determining the risk levels of patients after they are admitted to the emergency department could aid in making better patient care decisions. A recent retrospective study conducted at Maastricht UMC+ presented a new clinical risk score called the RISKINDEX. This score employs an AI model to predict the 31-day mortality of patients who visit the emergency department. The RISKINDEX surpassed the performance of internal medicine specialists; however, the extent of its beneficial value when applied in clinical practice was still uncertain. This led to the MARS-ED clinical trial, where the diagnostic accuracy, policy changes, and clinical impact of the RISKINDEX are determined on a large scale. The outcomes of this trial could revolutionize how we prioritize care in critical settings and even made the list of Nature Medicine Top Clinical Trials for 2024.