Bleeding disorders such as von Willebrand disease and hemophilia are conditions that occur when the blood cannot clot properly.
Because the clinical burden, societal impact and economic impact of mild and severe bleeding disorders are not as clearly understood, I will
apply novel biostatistical and machine learning methods to help understand and predict the risk of bleeding disorders,
apply novel causal inference methods to evaluate the effect of clinical interventions on the risk of bleeding disorders, and
learn if individualized treatment regimes are effective for personalized decision-making.
We are in the first stage of the project. I have been working on objective 1) by designing the study and applying state-of-the-art biostatistical and machine learning methods to predict risk of having a bleeding disorder as a function of patients’ characteristics. For instance, I was able to successfully and accurately predict that a young woman with specific characteristics will develop menstrual bleeding disorder.