Projects
Prediction of gait neuromechanics following orthopedic interventions in children with cerebral palsy using computer simulations based on personalized models KU Leuven
Children with cerebral palsy (CP) suffer from a brain lesion that leads to impaired motor control, spasticity and muscle weakness. All these factors undermine the subjects' gait performance and, with time, will pose limitation to their mobility, independence and self-care. Orthopedic interventions aim at improving the walking performance. However, functional outcomes are not always as expected and, often, follow up surgery is needed to ...
A novel molecular and personalized prognostic and predictive approach to inflammatory bowel diseases KU Leuven
The inflammatory bowel diseases (IBD) represent a spectrum of chronic immune-mediated disorders of the gut and extra-intestinal organs with Crohn's disease (CD) and ulcerative colitis (UC) as the two main phenotypes. There is substantial inter-individual variability in the clinical presentation and the outcome of IBD. Despite the important progress in therapeutic discovery, clinical and mucosal remission rates leave large margins for ...
Predicting outcomes of inflammatory bowel diseases: creating opportunities for personalized medicine KU Leuven
The imminent introduction of new therapies for both Crohn’s disease (CD) and ulcerative colitis (UC), will have a huge impact on our clinical practice in the coming years. However, it is anticipated that clinical response to each of these agents will vary significantly between individuals. Furthermore, these new therapies are expensive and long-term use may be associated with adverse events. Another important drawback for treatment with ...
Personalized Prediction and Intervention for Behavioral Avoidance and Maladaptive Affective States KU Leuven
Accurate forward prediction of maladaptive behaviors and emotional states involved in various forms of psychopathology offers an intriguing avenue for prevention and intervention science. To date, however, such prediction has been limited by a heterogeneity in factors determining individuals' behaviors and emotions. To address this limitation, the proposed project adopts an idiographic (i.e., person specific) approach while focusing on two ...
A whole-body physiologically based pharmacokinetic model for personalized 161Tb-PRRT KU Leuven
Peptide receptor radionuclide therapy (PRRT) has been proven to be a safe and effective treatment of somatostatin receptor expressing neuroendocrine tumours (NETs). So far, standard activities are usually injected, although it has been shown that the variable tumour burden between patients can have a high impact on the biologically effective doses (BEDs) to normal tissues and tumour tissue with large tumour loads leading to a considerably ...
Clinical risk prediction models based on multicenter data: methods for model development and validation KU Leuven
Risk prediction models are developed to assist doctors in diagnosing patients, decision-making, counseling patients or providing a prognosis. To enhance the generalizability of risk models, researchers increasingly collect patient data in different settings and join forces in multicenter collaborations. The resulting datasets are clustered: patients from one center may have more similarities than patients from different centers, for example, ...
Developing process analytics-based real-time personalized feedback for smart learning environments KU Leuven
User modeling for personalized Ad retrieval KU Leuven
The era of Social Media-as we know it today-started around the early 2000s. Social media enable a form of virtual content sharing that is fundamentally different than before. Social media content is no longer created and published by specific individuals, but instead is continuously modified by all users in a collaborative fashion. Nowadays, users around the world are taking advantage of social media as one of their key components of ...
Personalized therapy for lung cancer patients using respiratory impedance models Ghent University
This project proposes a general identification framework in cancer patients based on modeling of tumor growth and modeling of respiratory impedance for further prediction of an individualized lung cancer therapy/treatment. The hypothesis of the research context is that the non-invasive nonmaneuver
forced oscillation technique can provide useful information about the respiratory function in lung cancer patients before and after treatment ...