Predictive Models: Machine learning algorithms can develop predictive models to forecast an individual's risk of developing hypercoagulability or DVT based on a combination of genetic, lifestyle, and clinical factors.
The goal of this project is to use machine learning to find important factors causing Deep Vain Thrombosis in patients using data from the UK Biobank. Part of the challenge is to use tha data efficientlly by analyizing and reconstruct the data to fit the best possible model.
Deep Vein Thrombosis, also known as DVT, is a condition where a blood clot is formed in a central vein in the leg or arm. If the clot breaks off and travels to the heart or brain, it can cause a pulmonary embolism or stroke.
The project will use a variety of machine learning techniques to identify important factors causing the condition. The results of the project will be used to improve the diagnosis of DVT