I am seeking to build an Artificial Intelligence via Python that recognizes patterns in detecting early signs of disease, as the goal to prevent the disease. I want to use Supervised Learning. I was wondering if I should use Classification or Regression. The images I input are basically images from for example X-Ray where I have input in the information in the potential early stages of a patient’s disease, about whether it is a disease or not. And since it’s supervised learning, I have also output images of diseases and non-diseases which the machine trains on. In the end, I want to have the AI know from analyzing a picture whether it is a disease or not with great accuracy.
At the moment I am doing research. What concepts, subjects should I focus on?
Also, how much computing power is required for this? For example, if we have 50.000 pictures to analyze. I am trying this in Jupyter Notebook. Are there any more important factors that I need to know in order to make my project a reality? I am a beginner ANY help, tips would be APPRECIATED!