Projects We Care 2020
In 2020, the collaboration between Tilburg University and the Elisabeth-TweeSteden Hospital was expanded with the We Care program. We Care makes annual funding available for research projects in which doctors and scientists work together. In 2020 six projects were awarded funding.
Summary of the We Care 2020 projects
1. Using Artificial Intelligence for Early Diagnosis of Alzheimer Disease
dr. Spyros Angelopoulos, TiSEM
dr. Gerwin Roks, neurology (ETZ)
Alzheimer’s Disease (AD) is the second most common reason for death in the Netherlands, with more than 44 million people worldwide suffering from it. Novel treatments for AD focus on the early stages of the disease, making early diagnosis essential. This project aims to build an Artificial Intelligence (AI) computer aided diagnosis (CAD) framework to early diagnose AD from magnetic resonance imaging (MRI). An AI-CAD framework can improve AD diagnosis at early stages and enable practitioners to further explore the development of the disease and study the factors that cause its deterioration. If an AI-CAD framework is successful for the early diagnosis of AD, it creates the potential to assist clinicians in other disease diagnoses.
2. We-Care-Mind: E-health intervention in women with pregnancy distress: a randomized controlled trial
prof. dr. Victor Pop, TSB
dr. Steven Koenen, perinatology (ETZ)
During pregnancy, women are at risk for mental health problems: up to 20% present with distress symptoms (depression and / or anxiety) with negative impact on maternal and fetal well-being. Mindfulness-based interventions (MBI’s) are increasingly being used to treat symptoms of stress, anxiety and depression. The current WeCare study, as part of a large birth cohort study in which up to 10.000 pregnant women are prospectively followed (the Brabant Study), aims to examine the effectiveness of an online mindfulness intervention to reduce distress during pregnancy. e-Health interventions for mental health problems in general have become increasingly popular during the last decades, they are cheap and accessible to the whole population.
3. Using Artificial Intelligence to predict outcome after trauma
dr. Katrijn van Deun, TSB
dr. Koen Lansink, trauma surgery (ETZ)
Trauma, defined as a physical injury, is a leading cause of death and disability. The prediction of (non-)fatal outcome after trauma can possibly be improved with AI techniques. In subproject 1 we want to develop a survival prediction model for the Dutch trauma population using AI. In subproject 2 we want to predict outcomes after non-fatal trauma. Implementation of these models can lead to better policy choices and improvement of trauma care.
4. Improving effectiveness of multidisciplinary team meetings (MDTM) in oncology
prof.dr. Roger Leenders, TSB
dr. Alexander Schouten, TSHD
dr. Laurens Beerepoot, internal medicine / oncology (ETZ)
Cancer treatment is done in multidisciplinary teams. Effective MDTM’s are of interest for optimal patient care. In this study we use an innovative research approach: dynamic social network analysis--an advanced statistical approach that makes it possible to uncover fine-grained social interaction processes and routines that distinguish MDTM’s from each other. With this knowledge we may be able to optimize MDTM performance for better patient outcome.
5. Cancer Survivors Back on Track; making shared decisions about personalized supportive care for cancer survivors
dr. Margot Joosen, Tranzo, TSB
dr. Dareczka Wasowicz, gastrointestinal surgery (ETZ)
Due to better screening technologies and more effective treatment options, the number of cancer survivors continues to grow. As a result, an increasing number of cancer survivors faces challenges in resuming life after treatment. Current supportive care after treatment, however, seems fragmented and insufficiently tailored to individual values and needs.
In this project an online tool ‘Back on Track’ is developed to support cancer survivors and healthcare professionals in making shared decisions about personalized supportive care after primary treatment. By means of a qualitative interview- and focus group study among cancer survivors, healthcare professionals and other stakeholders, experiences, needs and values will be investigated and 'Back on Track' will be developed in co-creation with the target users. In this way, the project contributes to the realization of better support for cancer survivors in resuming life after cancer.
6. Personalized Cognitive Diagnostics for Early and Adequate Detection of Dementia
dr. Marijn van Wingerden, TSHD
dr. Ruth Mark, TSB
dr. Hetty Scholten, medical psychology (ETZ)
The early detection of dementia is vital as it allows patients, caregivers and care professionals time to make adaptations and schedule interventions. At the same time, dementia is very hard to detect, because cognitive capacities are different between individuals. To solve this issue, a new online memory test will be developed in this project, that can contribute to the early detection of dementia. In this test, based on famous faces, artificial intelligence is used to predict a user-specific cognitive profile. This will allow a more sensitive detection of impairments, and thus allow earlier detection of possible dementia.
More Information: www.mindify.nl