Professor of Intensive Care, Senior medical specialist
Prof. dr. M.S. (Sesmu) Arbous
Area(s) of expertise:
Anesthesiologist-intensivist
Anesthesiologist-intensivist
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Introduction
I have been an anesthesiologist since 2003 and an intensivist since 2005, working in the ICU at Leiden University Medical Center. As a senior staff member, I focus on sepsis and acute liver failure. I am also trained as a clinical epidemiologist (MSc).
In 1998, I obtained my PhD cum laude on anesthesia-related risk factors for perioperative morbidity and mortality. Since April 1, 2024, I have been Professor of Intensive Care Medicine, focusing on integrating technology into patient care; my inaugural lecture was delivered on July 4, 2025.
From 2009 to 2025, I served as Residency Program Director. Since 2017, I have been Program Director of the MSc Technical Medicine and track coordinator Sensing & Stimulation (Leiden-Delft-Erasmus). I am also a board member of NICE and member of the NVIC Strategic Information Policy Network, focused on using clinical data to improve ICU care.
In 1998, I obtained my PhD cum laude on anesthesia-related risk factors for perioperative morbidity and mortality. Since April 1, 2024, I have been Professor of Intensive Care Medicine, focusing on integrating technology into patient care; my inaugural lecture was delivered on July 4, 2025.
From 2009 to 2025, I served as Residency Program Director. Since 2017, I have been Program Director of the MSc Technical Medicine and track coordinator Sensing & Stimulation (Leiden-Delft-Erasmus). I am also a board member of NICE and member of the NVIC Strategic Information Policy Network, focused on using clinical data to improve ICU care.
Scientific research
My research focuses on data-driven, technology-supported intensive care, aiming to deliver personalized and future-proof care. It centers on leveraging clinical data from the ICU and beyond (e.g., ELAN) to generate actionable insights and support decision-making. I develop and implement AI-based decision support tools to predict hemodynamic deterioration, infections, and outcomes, with emphasis on clinical usability and workflow integration.
A key priority is bridging the implementation gap by demonstrating real-world impact on decision-making, workload, and patient outcomes, in collaboration with clinical, technical, and data science partners.
This work aligns with the LUMC “Digital Close” strategy and LUMC@Home program, including applications such as the ICU RecoverBox. Responsible and ethical AI use is central, focusing on transparency, validity, bias, and clinical value.
A key priority is bridging the implementation gap by demonstrating real-world impact on decision-making, workload, and patient outcomes, in collaboration with clinical, technical, and data science partners.
This work aligns with the LUMC “Digital Close” strategy and LUMC@Home program, including applications such as the ICU RecoverBox. Responsible and ethical AI use is central, focusing on transparency, validity, bias, and clinical value.
