Osteoporosis Detection App

In this project, I aimed to apply AI/machine learning to design code capable of analyzing and predicting the stage in progression of osteoporosis given a patient's data. In order for this code to work, I first loaded in a large array of patient osteoporosis data containing knee x-ray scans and general health files (age, gender, weight, BMI). By applying general statistical analysis, I was then able to summarize the large amounts of data and store it for later use. I then applied general machine learning concepts such as, neural networking and classification, with the combination of the summarized data, to be able to further break down x-ray images and patient statistics to generate a diagnosis in the form of an sophisticated prediction. Ultimately, my app was able to generate predictions yielding 30-40% accuracy. This app will still need work and I look to better my understanding of the osteoporosis disease as well as, python, to improve this app.