Projects
Dynamic modelling of human progressive lung fibrosis in a human lung on a chip KU Leuven
LogiCare Tetra AI Thomas More
Mold-active Azoles: Development, Validation and Implementation of strategies for Safe and Effective Dosing (M-ADVISED) KU Leuven
Infections, including severe bacterial infections and invasive fungal infections, are a major cause of morbidity and mortality in critically ill patients and other patient populations (i.e. patients with hematological malignancies). Therapeutic exposure to antibacterial or antifungal drugs at the site of infection (or in plasma as a surrogate matrix) is crucial for successful treatment of severe bacterial and fungal infections. However, it ...
Validating the application of a first-in-class human serum-functional immunodynamic status (sFIS) assay as bona fide immuno-oncology biomarker KU Leuven
Objectifying performance assessments and personalized rehabilitation trajectories to improve return to work in failed back surgery patients. KU Leuven
The primary scientific objective of the study is to examine if a personalized biopsychosocial rehabilitation program specifically targeting RTW is more effective in improving the physical ability to
work in FBSS patients after SCS implantation compared with usual care. The secondary objective of the study is to examine if a personalized biopsychosocial rehabilitation program specifically targeting
RTW compared with usual care is ...
Computational Time Series Analysis for Cardiovascular Health and Cardiopulmonary Fitness Profiling KU Leuven
To date, there is an unmet need for accurate computational models that can identify and manage individuals at high risk of developing adverse Cardiovascular (CV) events. The purpose of this doctoral project, is the utilization of machine and deep learning algorithms to create a computational pipeline to construct a profile of patients related to their CV health and fitness and predict their response to potential exercise treatment programmes. ...
Mixed-initiative explanation methods: towards the next generation of interactive machine learning steered with rich feedback of non-expert users KU Leuven
The overall objective of this project is to enable non-expert users to interact with ML models as a basis to improve the accuracy of such models and to increase user trust. As individual users have different needs, the long-term goal of our research is to personalise mixed-initiative explanation interfaces to the specific needs, characteristics, and context of each user.
Multiple sclerosis immunogenetics: moving to multi-omics single-cell resolution KU Leuven
Multiple sclerosis (MS) is an autoimmune disease of the central nervous system that affects 2.5 million people worldwide and leads to important physical and cognitive disability with typical onset during young adulthood. Over the past years, the Laboratory for Neuroimmunology (KU Leuven) identified 233 MS genetic risk factors, which are shared with other autoimmune but not neurological disorders and implicate specific immune cells in the ...
ERA-NET RUS.PLUS - JTC 2019: NANOtechnological TOolkit for multiplexed 3D detection and monitoring of BIOmarker status in breast cancer biopsies Vrije Universiteit Brussel
must demonstrate its greater potential in personalised approaches. A prerequisite for this is the identification
of genetic and proteomic biomarkers as well as the use of novel immunological signatures that take into
account the complex three-dimensional (3D) architecture of the tumour.
For this purpose, NanoToBio is ...