Geometric deep learning

The goal of these course notes is to describe the main mathematical ideas behind geometric deep learning and to provide implementation details for several applications in shape analysis and synthesis, computer vision and computer graphics. The text in the course materials is primarily based on previously published work. With these notes we gather and provide a clear picture of the key concepts and techniques that fall under the umbrella of geometric deep learning, and illustrate the applications they enable. We also aim to provide practical implementation details for the methods presented in these works, as well as suggest further readings and extensions of these ideas

Herstelsteun in de verslavingszorg: Wat ga je er zelf aan doen?

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Vijf jaar 'routine outcome management' in de ambulante verslavingszorg

Three substance abuse treatment centres set up a benchmarking project for routine outcome management (ROM) of structured cognitive behavioral treatments for outpatients with a substance use disorder. To present the results of five years benchmarking. All patients were included at intake and the follow-up assessment was performed by a call-center nine months later. Twice a year aggregated data were fed back to management and treatment teams. Since 2005, clinical outcome data, including substance abuse data, have been collected for more than half of all 15.786 treated patients. At follow-up, nine months after intake, 23% was abstinent, 28% reported moderate substance use and 49% reported excessive substance use. The Dutch centres for the treatment of substance abuse were successful in setting up ROM projects to monitor and compare the development and the effects of outpatient addiction treatments. The clinical results are acceptable and correspond to the results of the American project called match. It is not yet clear whether the biannual feedback of aggregated outcomes to management and treatment teams has contributed to the creation of learning organisations, but it has provided transparency and has made it possible for teams to learn from the outcome