OPTIMAL: OsteoPorosis Treatment Identification using Machine Learning

We are doing developing a solution to identify people who are at risk of developing Osteoporosis (OP). OP is a health condition that weakens bones, making them fragile and more likely to break. It develops slowly over several years and is often only diagnosed when a fall or sudden impact causes a bone to break. We are interested in determining which patients are at risk of developing OP. We will do this by combining different types of data together including data from medical images called CT scans and data from patient's medical records. Using a techinque called machine learning we will develop a way of determining if someone is at risk of developing OP and provide an integrated platform improve the delivery of treatment by clinical teams. Using machine learning to predict which patients are at risk from their images and medical records means that we can prevent fractures by early treatment for OP. This will reduce the risk to patients of life limiting falls and should also reduce hospital admission for surgical management of fractures. We have assembled a multi-disciplinary team consisting of clinicians, data scientists and computer scientists to work together to find a way of identifying at risk patients.